# Module im Bereich: Applied Data Science

# AMS Lab Projects

##### every 


##### (in German: AMS Lab Projects )

<table bgcolor="#7FB3D9" border="1" id="bkmrk-%5Btitle%5D" style="width: 100%; border-collapse: collapse; border-width: 1px; border-style: none;"><colgroup><col style="width: 100%;"></col></colgroup><tbody><tr style="background-color: rgb(235, 243, 249);"><td>##### <span style="color: rgb(0, 104, 180);">**Module-ID:** </span><span style="color: rgb(0, 104, 180);">**FIN-INF-120503** </span>

</td></tr></tbody></table>

<table bgcolor="#7FB3D9" border="1" id="bkmrk-" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 13.061%;"></col><col style="width: 15.442%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col></colgroup><tbody><tr><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Abbreviation**</span>

<span style="color: rgb(61, 61, 61);">AMS-Lab </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Credit Points**</span>

<span style="color: rgb(61, 61, 61);">6 </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Semester**</span>

<span style="color: rgb(61, 61, 61);">every </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Term**</span>

<span style="color: #3d3d3d;">starting at 1. </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);">**<span style="color: rgb(61, 61, 61);">Duration</span>**

<span style="color: rgb(61, 61, 61);">1 Semester </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Language**</span>

<span style="color: rgb(61, 61, 61);">english</span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Level**</span>

<span style="color: rgb(61, 61, 61);">Master </span>

</td></tr></tbody></table>

<table border="1" id="bkmrk-verantwortung%3A-verwe" style="border-collapse: collapse; width: 100%; height: 124.8px; border-width: 1px; border-style: none;"><colgroup><col style="width: 24.7879%;"></col><col style="width: 75.2121%;"></col></colgroup><tbody><tr style="height: 35.4px;"><td style="height: 35.4px;">**Link:**</td><td style="height: 35.4px;">[ LSF](https://lsf.ovgu.de/qislsf/rds?state=wsearchv&search=1&subdir=veranstaltung&veranstaltung.semester=20261&veranstaltung.dtxt=AMS+Lab+Projects&P_start=0&P_anzahl=30&P.sort=veranstaltung.dtxt&_form=display "AMS Lab Projects")</td></tr><tr><td>**Limited accessability:**</td><td>false </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Responsibility:**</td><td style="height: 29.8px;">Prof. Dr.-Ing. Benjamin Noack </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Lecturer:**</td><td style="height: 29.8px;">Prof. Dr.-Ing. Benjamin Noack </td></tr><tr><td>**Classes:**</td><td>- *AMS Lab Projects*

 </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Applicability in curriculum:**</td><td style="height: 29.8px;">- M.Sc. INF: Informatik  
- M.Sc. INF: Schlüssel- und Methodenkompetenzen  
- M.Sc. INF: Informatik Wahlpflicht (SPO 2027)  
- M.Sc. INF: Schlüssel- und Methodenkompetenz (SPO 2027)  
- M.Sc. INF: Projekte (SPO 2027)  
- M.Sc. INGINF: Informatik  
- M.Sc. INGINF: Ingenieurinformatik  
- M.Sc. INGINF: Schlüssel- und Methodenkompetenzen  
- M.Sc. WIF: Informatik  
- M.Sc. WIF: Schlüssel- und Methodenkompetenzen  
- M.Sc. WIF: Informatik Wahlpflicht (SPO 2027)  
- M.Sc. WIF: Schlüssel- und Methodenkompetenz (SPO 2027)  
- M.Sc. WIF: Projekte (SPO 2027)  
- M.Sc. DKE: Applied Data Science  
- M.Sc. DKE: Projects (SPO 2027)  
- M.Sc. DE: Interdisziplinäres Team-Projekt  
- M.Sc. DE: Fachliche Spezialisierung  
- M.Sc. DE: Digital Engineering-Projekt  
- M.Sc. DE: Digital Engineering (SPO 2027)  
- M.Sc. DE: Engineering Specialization (SPO 2027)  
- M.Sc. DE: Schlüssel- und Methodenkompetenz (SPO 2027)  
- M.Sc. DE: Projekte (SPO 2027)  
- M.Sc. VC: Computer Science  
- M.Sc. VC: Schlüssel- und Methodenkompetenzen  
- M.Sc. VC: Computer Science (SPO 2027)  
- M.Sc. VC: Schlüssel- und Methodenkompetenz (SPO 2027)  
  
</td></tr></tbody></table>

**Intended learning outcomes:** Students who complete the course ...

- can collaborate in teams to solve challenges in technical domains and deepen their technical expertise.
- can manage a project and define goals and milestones
- can acquire the knowledge in a technical domain to derive solutions
- can present and document their work and achievements

  
**Content:** This module offers different team projects and individual projects on current, research-related areas like:

- robotics
- sensor data processing
- navigation and planning
- industrial machine learning
- optimization and control
- and more

**Workload:** 180 h of individual and team work

<table border="1" id="bkmrk-studien-%2Fpr%C3%BCfungslei" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 32.0641%;"></col><col style="width: 34.9204%;"></col><col style="width: 33.0155%;"></col></colgroup><tbody><tr><td>**Pre-examination requirements:**</td><td>**Type of examination:**</td><td>**Teaching method / lecture hours per week (SWS):**</td></tr><tr><td></td><td>Scientific Project (Wissenschaftliches Projekt)

</td><td>Project (2 SWS)

</td></tr></tbody></table>

<table border="1" id="bkmrk-voraussetzungen-nach" style="font-family: var(--font-body); font-size: 14px; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Prerequisites according to examination regulations:**</td><td>**Recommended prerequisites:**</td></tr><tr><td>keine

</td><td></td></tr></tbody></table>

<table border="1" id="bkmrk-medienformen%3A-litera" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Media:**</td><td>**Literature:**</td></tr><tr><td></td><td>Literature will be announced in the lecture.

</td></tr></tbody></table>

**Comments:**

# Advanced Programming in Computational Intelligence in Games

##### Summer 


##### (in German: Advanced Programming in Computational Intelligence in Games )

<table bgcolor="#7FB3D9" border="1" id="bkmrk-%5Btitle%5D" style="width: 100%; border-collapse: collapse; border-width: 1px; border-style: none;"><colgroup><col style="width: 100%;"></col></colgroup><tbody><tr style="background-color: rgb(235, 243, 249);"><td>##### <span style="color: rgb(0, 104, 180);">**Module-ID:** </span><span style="color: rgb(0, 104, 180);">**FIN-INF-120495** </span>

</td></tr></tbody></table>

<table bgcolor="#7FB3D9" border="1" id="bkmrk-" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 13.061%;"></col><col style="width: 15.442%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col></colgroup><tbody><tr><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Abbreviation**</span>

<span style="color: rgb(61, 61, 61);">AP-CIG </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Credit Points**</span>

<span style="color: rgb(61, 61, 61);">6 </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Semester**</span>

<span style="color: rgb(61, 61, 61);">Summer </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Term**</span>

<span style="color: #3d3d3d;">starting at 1. </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);">**<span style="color: rgb(61, 61, 61);">Duration</span>**

<span style="color: rgb(61, 61, 61);">1 Semester </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Language**</span>

<span style="color: rgb(61, 61, 61);">english</span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Level**</span>

<span style="color: rgb(61, 61, 61);">Master </span>

</td></tr></tbody></table>

<table border="1" id="bkmrk-verantwortung%3A-verwe" style="border-collapse: collapse; width: 100%; height: 124.8px; border-width: 1px; border-style: none;"><colgroup><col style="width: 24.7879%;"></col><col style="width: 75.2121%;"></col></colgroup><tbody><tr style="height: 35.4px;"><td style="height: 35.4px;">**Link:**</td><td style="height: 35.4px;">[ LSF](https://lsf.ovgu.de/qislsf/rds?state=wsearchv&search=1&subdir=veranstaltung&veranstaltung.semester=20261&veranstaltung.dtxt=Advanced+Programming+in+Computational+Intelligence+in+Games&P_start=0&P_anzahl=30&P.sort=veranstaltung.dtxt&_form=display "Advanced Programming in Computational Intelligence in Games")</td></tr><tr><td>**Limited accessability:**</td><td></td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Responsibility:**</td><td style="height: 29.8px;">Sanaz Mostaghim </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Lecturer:**</td><td style="height: 29.8px;">Sanaz Mostaghim </td></tr><tr><td>**Classes:**</td><td>- Lecture *Advanced Programming in Computational Intelligence in Games*
- Tutorials *Advanced Programming in Computational Intelligence in Games*

 </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Applicability in curriculum:**</td><td style="height: 29.8px;">- M.Sc. INF: Informatik  
- M.Sc. INGINF: Informatik  
- M.Sc. WIF: Informatik  
- M.Sc. DKE: Applied Data Science  
- M.Sc. VC: Computer Science  
  
</td></tr></tbody></table>

**Intended learning outcomes:** Students ...

- carry out a large programming project using the concepts from the theoretical part of the course.
- have a full understanding of the algorithms of computational Intelligence in Games.
- learn to develop new ideas and apply them to new problems in the context of AI and Games.
- learn to program the methodologies from the lectures in teams.

  
**Content:** This course addresses the basic and advanced topics in the area of computational intelligence and games and contains three parts: Part 1 addresses the basics in Evolutionary Game Theory (EGT). In this part you will learn about simple games such as scissors/rock/paper and the focus on the strategies for playing games. Part 2 is about learning agents, and we focus on reinforcement learning mechanisms. There are three questions for games:

- How can we use the information from a search mechanism to learn?
- How can we use reinforcement learning to find for a better strategy?
- How can we use reinforcement learning as a search mechanism?

The application is on board games. Part 3 contains the advanced topics in games and artificial intelligence How can we consider physical constraints of a spaceship while moving in an unknown terrain. Other topics are Monte Carlo Tree Search, Procedural Content Generation, Decision Making and Multi-Objective Learning. **Workload:** 56 contact hours + 94h self study

<table border="1" id="bkmrk-studien-%2Fpr%C3%BCfungslei" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 32.0641%;"></col><col style="width: 34.9204%;"></col><col style="width: 33.0155%;"></col></colgroup><tbody><tr><td>**Pre-examination requirements:**</td><td>**Type of examination:**</td><td>**Teaching method / lecture hours per week (SWS):**</td></tr><tr><td></td><td>- Hausarbeit (home work containing programming)
- Exercises and Tutorials
- Klausur (written Exam) 120 Minuten

</td><td>- lectures (2 SWS)
- exercise classes (2 SWS)

</td></tr></tbody></table>

<table border="1" id="bkmrk-voraussetzungen-nach" style="font-family: var(--font-body); font-size: 14px; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Prerequisites according to examination regulations:**</td><td>**Recommended prerequisites:**</td></tr><tr><td>none

</td><td>Programming experience

</td></tr></tbody></table>

<table border="1" id="bkmrk-medienformen%3A-litera" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Media:**</td><td>**Literature:**</td></tr><tr><td></td><td>- ­Ian Millington and John Funge, Artificial Intelligence for Games, CRC Press, 2009
- Richard S. Sutton and Andrew G. Barto, Reinforcement Learning: An Introduction, MIT Press, Cambridge, MA, 1998
- Jorgen W. Weibull, Evolutionary Game Theory, MIT Press, 1997
- Thomas Vincent, Evolutionary Game Theory, Natural Selection, and Darwinian Dynamics, Cambridge University Press, 2005
- Josef Hofbauer, Karl Sigmund, Evolutionary Games and Population Dynamics, Cambridge University Press, 1998

  
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**Comments:**

# Advanced Topics in Deep Learning (Master)

##### every 


##### (in German: Advanced Topics in Deep Learning (Master) )

<table bgcolor="#7FB3D9" border="1" id="bkmrk-%5Btitle%5D" style="width: 100%; border-collapse: collapse; border-width: 1px; border-style: none;"><colgroup><col style="width: 100%;"></col></colgroup><tbody><tr style="background-color: rgb(235, 243, 249);"><td>##### <span style="color: rgb(0, 104, 180);">**Module-ID:** </span><span style="color: rgb(0, 104, 180);">**FIN-INF-120496** </span>

</td></tr></tbody></table>

<table bgcolor="#7FB3D9" border="1" id="bkmrk-" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 13.061%;"></col><col style="width: 15.442%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col></colgroup><tbody><tr><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Abbreviation**</span>

<span style="color: rgb(61, 61, 61);">ATDL </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Credit Points**</span>

<span style="color: rgb(61, 61, 61);">6 </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Semester**</span>

<span style="color: rgb(61, 61, 61);">every </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Term**</span>

<span style="color: #3d3d3d;">starting at 1. </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);">**<span style="color: rgb(61, 61, 61);">Duration</span>**

<span style="color: rgb(61, 61, 61);">1 Semester </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Language**</span>

<span style="color: rgb(61, 61, 61);">english</span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Level**</span>

<span style="color: rgb(61, 61, 61);">Master </span>

</td></tr></tbody></table>

<table border="1" id="bkmrk-verantwortung%3A-verwe" style="border-collapse: collapse; width: 100%; height: 124.8px; border-width: 1px; border-style: none;"><colgroup><col style="width: 24.7879%;"></col><col style="width: 75.2121%;"></col></colgroup><tbody><tr style="height: 35.4px;"><td style="height: 35.4px;">**Link:**</td><td style="height: 35.4px;">[ LSF](https://lsf.ovgu.de/qislsf/rds?state=wsearchv&search=1&subdir=veranstaltung&veranstaltung.semester=20261&veranstaltung.dtxt=Advanced+Topics+in+Deep+Learning+(Master)&P_start=0&P_anzahl=30&P.sort=veranstaltung.dtxt&_form=display "Advanced Topics in Deep Learning (Master)")</td></tr><tr><td>**Limited accessability:**</td><td></td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Responsibility:**</td><td style="height: 29.8px;">Sebastian Stober </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Lecturer:**</td><td style="height: 29.8px;">Sebastian Stober </td></tr><tr><td>**Classes:**</td><td>*Advanced Topics in Deep Learning* </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Applicability in curriculum:**</td><td style="height: 29.8px;">- M.Sc. INF: Informatik  
- M.Sc. INGINF: Informatik  
- M.Sc. WIF: Informatik  
- M.Sc. DKE: Learning Methods and Models for Data Science  
- M.Sc. DKE: Data Processing for Data Science  
- M.Sc. DKE: Applied Data Science  
- M.Sc. DE: Methoden der Informatik  
- M.Sc. VC: Computer Science  
  
</td></tr></tbody></table>

**Intended learning outcomes:** Students ...

- can read and analyze current research papers
- apply deep learning to an application domain
- gain in-depth knowledge In the application domain
- learn to work efficiently in a team on scientific problems
- learn to work on a server infrastructure
- present scientific results in a written and oral form

  
**Content:**

- Current topics from deep learning research
- Create domain-specific deep learning pipelines
- The application domain will be announced  
    beforehand

**Workload:**

- 30h in person
- 150h self-study

  
<table border="1" id="bkmrk-studien-%2Fpr%C3%BCfungslei" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 32.0641%;"></col><col style="width: 34.9204%;"></col><col style="width: 33.0155%;"></col></colgroup><tbody><tr><td>**Pre-examination requirements:**</td><td>**Type of examination:**</td><td>**Teaching method / lecture hours per week (SWS):**</td></tr><tr><td></td><td>- Hausarbeit
- Mündliche Prüfung

</td><td>Vorlesung/Seminar (2 SWS)

</td></tr></tbody></table>

<table border="1" id="bkmrk-voraussetzungen-nach" style="font-family: var(--font-body); font-size: 14px; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Prerequisites according to examination regulations:**</td><td>**Recommended prerequisites:**</td></tr><tr><td>none

</td><td>Introduction to Deep Learning

</td></tr></tbody></table>

<table border="1" id="bkmrk-medienformen%3A-litera" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Media:**</td><td>**Literature:**</td></tr><tr><td></td><td></td></tr></tbody></table>

**Comments:**

# Assistenzrobotik

**Sommer**


(engl. Assistance robotics )

<table bgcolor="#7FB3D9" border="1" id="bkmrk-%5Btitle%5D" style="width: 100%; border-collapse: collapse; border-width: 1px; border-style: none;"><colgroup><col style="width: 100%;"></col></colgroup><tbody><tr style="background-color: rgb(235, 243, 249);"><td>##### <span style="color: rgb(0, 104, 180);">**Modulnummer: FIN-INF-120443** </span>

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<table bgcolor="#7FB3D9" border="1" id="bkmrk-" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 13.061%;"></col><col style="width: 15.442%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col></colgroup><tbody><tr><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Kürzel**</span>

<span style="color: rgb(61, 61, 61);">AROB </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**CP**</span>

<span style="color: rgb(61, 61, 61);">6 </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Semester**</span>

<span style="color: rgb(61, 61, 61);">Sommer </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Fachsem.**</span>

<span style="color: #3d3d3d;">ab 1. </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);">**<span style="color: rgb(61, 61, 61);">Dauer</span>**

<span style="color: rgb(61, 61, 61);">1 Semester </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Sprache**</span>

<span style="color: rgb(61, 61, 61);">deutsch</span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Niveau**</span>

<span style="color: rgb(61, 61, 61);">Master </span>

</td></tr></tbody></table>

<table border="1" id="bkmrk-verantwortung%3A-verwe" style="border-collapse: collapse; width: 100%; height: 89.3907px; border-width: 1px; border-style: none;"><colgroup><col style="width: 20.2601%;"></col><col style="width: 79.7399%;"></col></colgroup><tbody><tr><td>**Link zum LSF:**</td><td>[ LSF](https://lsf.ovgu.de/qislsf/rds?state=wsearchv&search=1&subdir=veranstaltung&veranstaltung.semester=20261&veranstaltung.dtxt=Assistenzrobotik&P_start=0&P_anzahl=30&P.sort=veranstaltung.dtxt&_form=display "Assistenzrobotik")</td></tr><tr><td>**Zugang beschränkt:**</td><td></td></tr><tr style="height: 29.7969px;"><td style="height: 29.7969px;">**Verantwortung:**</td><td style="height: 29.7969px;">Norbert Elkmann (Fraunhofer IFF) </td></tr><tr style="height: 29.7969px;"><td style="height: 29.7969px;">**Dozent:in:**</td><td style="height: 29.7969px;">Norbert Elkmann (Fraunhofer IFF) </td></tr><tr><td>**Lehrveranstaltungen:**</td><td>- Vorlesung *Assistenzrobotik*
- Übung *Assistenzrobotik*

</td></tr><tr style="height: 29.7969px;"><td style="height: 29.7969px;">**Verwendbarkeit:**</td><td style="height: 29.7969px;">- M.Sc. INF: Informatik  
- M.Sc. INF: Informatik Wahlpflicht (SPO 2027)  
- M.Sc. INGINF: Informatik  
- M.Sc. DKE: Applied Data Science  
- M.Sc. DE: Methoden des Digital Engineering  
- M.Sc. DE: Methoden der Informatik  
- M.Sc. DE: Fachliche Spezialisierung  
- M.Sc. DE: Informatik Wahlpflicht (SPO 2027)  
- M.Sc. DE: Digital Engineering (SPO 2027)  
- M.Sc. DE: Engineering Specialization (SPO 2027)  
  
</td></tr></tbody></table>

**Angestrebte Lernergebnisse:** Absolvent\*innen dieses Moduls ...

- kennen mathematische Transformationen zur geometrischen und differentiellen Beschreibung von Roboterkinematiken
- kennen die Bewegungsgleichung von Roboter-Manipulatoren und können sie für Fragestellungen zur kollaborativen Sicherheit anwenden
- kennen die unterschiedlichen Interpolationsarten zum Beschreiben einer Roboterbahn und können eigenständig C²-Trajektorien generieren
- können die Kinematik von mobilen Robotern modellieren und ihre Position unter Berücksichtigung von Unsicherheiten im Raum bestimmen
- kennen verschiedene Methoden des maschinellen Lernens (unüberwachtes und überwachtes Lernen sowie Deep Learning) und können deren Einsatzmöglichkeiten für die Bildverarbeitung im Kontext der Robotik einordnen
- verstehen die Grundprinzipien des Reinforcement Learnings und wissen, wie damit optimale Handhabungsstrategien für Roboter generiert werden können
- kennen die Grundlagen der Maschinensicherheit (Risikobeurteilung und CE-Kennzeichnung)
- kennen die Sicherheitsbetriebsarten für kollaborative Robotersysteme und können sie anwenden

  
**Inhalt:**

- Einführung in die Assistenzrobotik
- Grundlagen der Assistenzrobotik (Modellierung von Roboterkinematiken, Bahnplanung, Bewegungs- und Kraftregelung, Sensoren, mobile Systeme)
- Mensch-Roboter-Kollaboration und Sicherheit: Technologien, Maschinensicherheit, Normen, Rechtslage
- KI-Verfahren in der Robotik

**Arbeitsaufwand:** 42h Präsenzzeit + 138h selbstständige Arbeit

<table border="1" id="bkmrk-studien-%2Fpr%C3%BCfungslei" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 32.6591%;"></col><col style="width: 35.9941%;"></col><col style="width: 31.3468%;"></col></colgroup><tbody><tr><td>**Prüfungsvorleistungen:**</td><td>**Studien-/Prüfungsleistungen:**</td><td>**Lehrform / SWS:**</td></tr><tr><td style="vertical-align: top;"></td><td class="align-left" style="vertical-align: top;">Mündliche Prüfung

</td><td class="align-left" style="vertical-align: top;">- 2 SWS Vorlesung
- 2 SWS Übung

  
</td></tr></tbody></table>

<table border="1" id="bkmrk-voraussetzungen-nach" style="font-family: var(--font-body); font-size: 14px; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Voraussetzungen nach Prüfungsordnung:**</td><td>**Empfohlene Voraussetzungen:**</td></tr><tr><td class="align-left" style="vertical-align: top;">keine

</td><td class="align-left" style="vertical-align: top;">- Programmierkenntnisse
- Lineare Algebra

  
</td></tr></tbody></table>

<table border="1" id="bkmrk-medienformen%3A-litera" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Medienformen:**</td><td>**Literatur:**</td></tr><tr><td class="align-left" style="vertical-align: top;"></td><td class="align-left" style="vertical-align: top;"></td></tr></tbody></table>

**Hinweise:**

# Clean Code Development

##### Winter 


##### (in German: Clean Code Development )

<table bgcolor="#7FB3D9" border="1" id="bkmrk-%5Btitle%5D" style="width: 100%; border-collapse: collapse; border-width: 1px; border-style: none;"><colgroup><col style="width: 100%;"></col></colgroup><tbody><tr style="background-color: rgb(235, 243, 249);"><td>##### <span style="color: rgb(0, 104, 180);">**Module-ID:** </span><span style="color: rgb(0, 104, 180);">**FIN-INF-120432** </span>

</td></tr></tbody></table>

<table bgcolor="#7FB3D9" border="1" id="bkmrk-" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 13.061%;"></col><col style="width: 15.442%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col></colgroup><tbody><tr><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Abbreviation**</span>

<span style="color: rgb(61, 61, 61);">CCD </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Credit Points**</span>

<span style="color: rgb(61, 61, 61);">6 </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Semester**</span>

<span style="color: rgb(61, 61, 61);">Winter </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Term**</span>

<span style="color: #3d3d3d;">starting at 1. </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);">**<span style="color: rgb(61, 61, 61);">Duration</span>**

<span style="color: rgb(61, 61, 61);">1 Semester </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Language**</span>

<span style="color: rgb(61, 61, 61);">english</span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Level**</span>

<span style="color: rgb(61, 61, 61);">Master </span>

</td></tr></tbody></table>

<table border="1" id="bkmrk-verantwortung%3A-verwe" style="border-collapse: collapse; width: 100%; height: 124.8px; border-width: 1px; border-style: none;"><colgroup><col style="width: 24.7879%;"></col><col style="width: 75.2121%;"></col></colgroup><tbody><tr style="height: 35.4px;"><td style="height: 35.4px;">**Link:**</td><td style="height: 35.4px;">[ LSF](https://lsf.ovgu.de/qislsf/rds?state=wsearchv&search=1&subdir=veranstaltung&veranstaltung.semester=20262&veranstaltung.dtxt=Clean+Code+Development&P_start=0&P_anzahl=30&P.sort=veranstaltung.dtxt&_form=display "Clean Code Development")</td></tr><tr><td>**Limited accessability:**</td><td>true </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Responsibility:**</td><td style="height: 29.8px;">Prof. Dr. Frank Ortmeier </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Lecturer:**</td><td style="height: 29.8px;">Prof. Dr. Frank Ortmeier </td></tr><tr><td>**Classes:**</td><td>- Vorlesung *Clean Code Development*
- Übung *Clean Code Development*

 </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Applicability in curriculum:**</td><td style="height: 29.8px;">- M.Sc. INF: Informatik  
- M.Sc. INF: Schlüssel- und Methodenkompetenzen  
- M.Sc. INGINF: Informatik  
- M.Sc. INGINF: Schlüssel- und Methodenkompetenzen  
- M.Sc. DKE: Applied Data Science  
- M.Sc. DE: Methoden des Digital Engineering  
- M.Sc. DE: Methoden der Informatik  
- M.Sc. DE: Fachliche Spezialisierung  
- M.Sc. VC: Computer Science  
- M.Sc. VC: Schlüssel- und Methodenkompetenzen  
  
</td></tr></tbody></table>

**Intended learning outcomes:** Students:

- know and understand the principles of Clean Code Development
- are able to apply the associated tools and practices in practice
- learn to independently select and adapt the concepts suitable for a project
- learn to distribute tasks within a team and collaborate in an organized manner

  
**Content:**

- Software engineering deals with the creation and development of software, the organization and modeling of related data structures, and the operation of software systems. It thus encompasses software design, implementation, and management.
- The introductory lecture *Software Engineering I* provided the foundational knowledge for designing and writing good software.
- This advanced lecture introduces modern techniques and methods that are commonly used in the development of large software systems.
- We align with the four core values of *Clean Code Development* – evolvability, correctness, production efficiency, and comprehensibility.
- To achieve these goals, a variety of programming principles and practices will be introduced.
- These include, among others, team formation and organization in software development, principles and tools of Clean Code Development, continuous integration and automated build systems, bug tracking, error localization and debugging, automated and model-based testing, code analysis and quality metrics, requirements engineering and tracing, as well as distributed and component-based software architectures.
- The course will offer a high degree of practical engagement with tools and software development techniques, especially in the exercises. The goal is not only to convey abstract knowledge but also to develop hands-on competencies.
- Participation in the exercises is mandatory and will be conducted in groups.

**Workload:** 56h Präsenszeit + 124h selbständige Arbeit am Projekt

<table border="1" id="bkmrk-studien-%2Fpr%C3%BCfungslei" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 32.0641%;"></col><col style="width: 34.9204%;"></col><col style="width: 33.0155%;"></col></colgroup><tbody><tr><td>**Pre-examination requirements:**</td><td>**Type of examination:**</td><td>**Teaching method / lecture hours per week (SWS):**</td></tr><tr><td>Projekt

</td><td>Mündliche Prüfung

</td><td>- Vorlesung (2 SWS)
- Übung (2 SWS)

</td></tr></tbody></table>

<table border="1" id="bkmrk-voraussetzungen-nach" style="font-family: var(--font-body); font-size: 14px; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Prerequisites according to examination regulations:**</td><td>**Recommended prerequisites:**</td></tr><tr><td>keine

</td><td>Software Engineering

</td></tr></tbody></table>

<table border="1" id="bkmrk-medienformen%3A-litera" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Media:**</td><td>**Literature:**</td></tr><tr><td></td><td></td></tr></tbody></table>

**Comments:** Enrollment Restriction: Limited number of participants. The selection process will be announced during the first lecture.

# Data Science with Python

##### Winter 


##### (in German: Data Science with Python )

<table bgcolor="#7FB3D9" border="1" id="bkmrk-%5Btitle%5D" style="width: 100%; border-collapse: collapse; border-width: 1px; border-style: none;"><colgroup><col style="width: 100%;"></col></colgroup><tbody><tr style="background-color: rgb(235, 243, 249);"><td>##### <span style="color: rgb(0, 104, 180);">**Module-ID:** </span><span style="color: rgb(0, 104, 180);">**FIN-INF-120513** </span>

</td></tr></tbody></table>

<table bgcolor="#7FB3D9" border="1" id="bkmrk-" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 13.061%;"></col><col style="width: 15.442%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col></colgroup><tbody><tr><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Abbreviation**</span>

<span style="color: rgb(61, 61, 61);">DSWP </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Credit Points**</span>

<span style="color: rgb(61, 61, 61);">6 </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Semester**</span>

<span style="color: rgb(61, 61, 61);">Winter </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Term**</span>

<span style="color: #3d3d3d;">2. 

</span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);">**<span style="color: rgb(61, 61, 61);">Duration</span>**

<span style="color: rgb(61, 61, 61);">1 Semester </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Language**</span>

<span style="color: rgb(61, 61, 61);">english</span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Level**</span>

<span style="color: rgb(61, 61, 61);">Master </span>

</td></tr></tbody></table>

<table border="1" id="bkmrk-verantwortung%3A-verwe" style="border-collapse: collapse; width: 100%; height: 124.8px; border-width: 1px; border-style: none;"><colgroup><col style="width: 24.7879%;"></col><col style="width: 75.2121%;"></col></colgroup><tbody><tr style="height: 35.4px;"><td style="height: 35.4px;">**Link:**</td><td style="height: 35.4px;">[ LSF](https://lsf.ovgu.de/qislsf/rds?state=wsearchv&search=1&subdir=veranstaltung&veranstaltung.semester=20262&veranstaltung.dtxt=Data+Science+with+Python&P_start=0&P_anzahl=30&P.sort=veranstaltung.dtxt&_form=display "Data Science with Python")</td></tr><tr><td>**Limited accessability:**</td><td>false </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Responsibility:**</td><td style="height: 29.8px;">Dr. Christian Beyer </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Lecturer:**</td><td style="height: 29.8px;">Dr. Christian Beyer </td></tr><tr><td>**Classes:**</td><td>Data Science with Python </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Applicability in curriculum:**</td><td style="height: 29.8px;">- M.Sc. INF: Informatik  
- M.Sc. INF: Schlüssel- und Methodenkompetenzen  
- M.Sc. INGINF: Informatik  
- M.Sc. INGINF: Schlüssel- und Methodenkompetenzen  
- M.Sc. WIF: Informatik  
- M.Sc. WIF: Schlüssel- und Methodenkompetenzen  
- M.Sc. DKE: Applied Data Science  
- M.Sc. DE: Methoden der Informatik  
- M.Sc. DE: Interdisziplinäres Team-Projekt  
- M.Sc. VC: Computer Science  
- M.Sc. VC: Schlüssel- und Methodenkompetenzen  
  
</td></tr></tbody></table>

**Intended learning outcomes:** The course is about learning from data to perform predictions and obtain useful insights. In the seminar, we will use the programming language Python.  
Necessary skills to manage and analyze data will be taught and practiced on real-world applications. Programming knowledge from other courses is helpful but not mandatory. However, students are expected to have a profound knowledge of fundamental data-analysis techniques, such as classification, regression and clustering. After successful completion of this course, the student will be able to perform the following tasks in Python:

- Import and preprocess raw data (files, databases, web APIs)
- Transform data for modelling
- Perform exploratory data analysis with summary statistics and visualization
- Understand, build and evaluate predictive classification and regression models, including tree-based models, ensembles and boosted models
- Communicate and disseminate results and findings through reproducible documents, presentations, websites and interactive web applications

  
**Content:** Part Fundamentals &amp; Visualization: Basics, scripts, workflows, vectors &amp; functions in Python Explorative data visualization Data transformation Part Data Management &amp; Exploratory Data Analysis: Data cleaning &amp; scraping Generating hypotheses and an intuition about the data with exploratory data analysis Data import Data management Relational data Strings, categorical data, dates &amp; time Iteration: imperative &amp; functional programming Part Modeling: Linear regression Classification Evaluation Model selection &amp; regularization (LASSO, Ridge) Feature selection &amp; model interpretation Decision trees Ensembles: random forests Boosting: gradient boosted trees Unsupervised learning, e.g. k-means, hierarchical clustering, self-organizing maps, principal component analysis Topic modeling with simple graphical models Statistical testing Part Communication: Communication and dissemination of results through visualization and interpretable summaries with documents, notebooks, presentations &amp; websites

**Workload:** Attendance time = 28 h: - 2 SWS weekly seminar; Independent work outside the actual Seminar time = 152 h: - 76 h preparation and follow-up of the seminar topics - 76 h solving the tasks, incl. work in the laboratory 180h = 28h attendance time + 152h independent work

<table border="1" id="bkmrk-studien-%2Fpr%C3%BCfungslei" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 32.0641%;"></col><col style="width: 34.9204%;"></col><col style="width: 33.0155%;"></col></colgroup><tbody><tr><td>**Pre-examination requirements:**</td><td>**Type of examination:**</td><td>**Teaching method / lecture hours per week (SWS):**</td></tr><tr><td></td><td>Referat

</td><td>Seminar (2 SWS)

</td></tr></tbody></table>

<table border="1" id="bkmrk-voraussetzungen-nach" style="font-family: var(--font-body); font-size: 14px; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Prerequisites according to examination regulations:**</td><td>**Recommended prerequisites:**</td></tr><tr><td>keine

</td><td>Area 1: Data Mining, Machine Learning, Artificial Intelligence Area 2: Databases Area 3: Programming Languages and Software Engineering Area 4: Stochastics, Applied Statistics

</td></tr></tbody></table>

<table border="1" id="bkmrk-medienformen%3A-litera" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Media:**</td><td>**Literature:**</td></tr><tr><td></td><td>Will provided during the seminar

</td></tr></tbody></table>

**Comments:**

# Design-Projekt

**Sommer**


(engl. Design Project )

<table bgcolor="#7FB3D9" border="1" id="bkmrk-%5Btitle%5D" style="width: 100%; border-collapse: collapse; border-width: 1px; border-style: none;"><colgroup><col style="width: 100%;"></col></colgroup><tbody><tr style="background-color: rgb(235, 243, 249);"><td>##### <span style="color: rgb(0, 104, 180);">**Modulnummer: FIN-INF-120520** </span>

</td></tr></tbody></table>

<table bgcolor="#7FB3D9" border="1" id="bkmrk-" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 13.061%;"></col><col style="width: 15.442%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col></colgroup><tbody><tr><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Kürzel**</span>

<span style="color: rgb(61, 61, 61);">DSP </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**CP**</span>

<span style="color: rgb(61, 61, 61);">6 </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Semester**</span>

<span style="color: rgb(61, 61, 61);">Sommer </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Fachsem.**</span>

<span style="color: #3d3d3d;">ab 1. </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);">**<span style="color: rgb(61, 61, 61);">Dauer</span>**

<span style="color: rgb(61, 61, 61);">1 Semester </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Sprache**</span>

<span style="color: rgb(61, 61, 61);">deutsch</span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Niveau**</span>

<span style="color: rgb(61, 61, 61);">Master </span>

</td></tr></tbody></table>

<table border="1" id="bkmrk-verantwortung%3A-verwe" style="border-collapse: collapse; width: 100%; height: 89.3907px; border-width: 1px; border-style: none;"><colgroup><col style="width: 20.2601%;"></col><col style="width: 79.7399%;"></col></colgroup><tbody><tr><td>**Link zum LSF:**</td><td>[ LSF](https://lsf.ovgu.de/qislsf/rds?state=wsearchv&search=1&subdir=veranstaltung&veranstaltung.semester=20261&veranstaltung.dtxt=Design-Projekt&P_start=0&P_anzahl=30&P.sort=veranstaltung.dtxt&_form=display "Design-Projekt")</td></tr><tr><td>**Zugang beschränkt:**</td><td></td></tr><tr style="height: 29.7969px;"><td style="height: 29.7969px;">**Verantwortung:**</td><td style="height: 29.7969px;">Hans-Knud Arndt </td></tr><tr style="height: 29.7969px;"><td style="height: 29.7969px;">**Dozent:in:**</td><td style="height: 29.7969px;">Hans-Knud Arndt </td></tr><tr><td>**Lehrveranstaltungen:**</td><td>- Seminar *Design Projekt*
- Übung *Design Projekt*

</td></tr><tr style="height: 29.7969px;"><td style="height: 29.7969px;">**Verwendbarkeit:**</td><td style="height: 29.7969px;">- M.Sc. INF: Informatik  
- M.Sc. INF: Schlüssel- und Methodenkompetenzen  
- M.Sc. INGINF: Informatik  
- M.Sc. INGINF: Schlüssel- und Methodenkompetenzen  
- M.Sc. WIF: Wirtschaftsinformatik  
- M.Sc. WIF: Informatik  
- M.Sc. DKE: Applied Data Science  
- M.Sc. DE: Human Factors  
- M.Sc. VC: Schlüssel- und Methodenkompetenzen  
  
</td></tr></tbody></table>

**Angestrebte Lernergebnisse:** Absolvent\*innen dieses Moduls...

- entwickeln ein Verständnis für Industrie-Design
- setzen sich mit den „Zehn Thesen des Guten Designs“ von Dieter Rams auseinander und sind in der Lage diese auf Projekte anzuwenden
- entwickeln ein Verständnis für das Design aktueller IT-Produkte
- sind in der Lage, das Design von aktuellen IT-Produkte zu entwickeln und zu bewerten

  
**Inhalt:**

- Die Teilnehmer\*innen sollen im Rahmen dieser Lehrveranstaltung ihre neu gewonnenen Erkenntnisse in Bezug auf Design praktisch auf IT-Produkte anwenden. Hierbei werden die von Dieter Rams entwickelten „Zehn Thesen des Guten Designs“ eingesetzt.
- Darüber hinaus werden weitere Ansätze, wie zum Beispiel von John Maeda: "Simplicity: Die zehn Gesetze der Einfachheit" angewendet.

**Arbeitsaufwand:** Präsenzzeiten:

- 2 SWS Seminar = 28h
- 2 SWS Übung = 28h

Selbstständiges Arbeiten: - Vor- und Nachbereitung Vorlesung Entwicklung von Lösungen für die Übung 124h

180h = 4 SWS = 56h Präsenzzeit + 124h selbstständige Arbeit   
<table border="1" id="bkmrk-studien-%2Fpr%C3%BCfungslei" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 32.6591%;"></col><col style="width: 35.9941%;"></col><col style="width: 31.3468%;"></col></colgroup><tbody><tr><td>**Prüfungsvorleistungen:**</td><td>**Studien-/Prüfungsleistungen:**</td><td>**Lehrform / SWS:**</td></tr><tr><td style="vertical-align: top;"></td><td class="align-left" style="vertical-align: top;">Hausarbeit

</td><td class="align-left" style="vertical-align: top;">Seminar (2 SWS)  
Übung (2 SWS)

</td></tr></tbody></table>

<table border="1" id="bkmrk-voraussetzungen-nach" style="font-family: var(--font-body); font-size: 14px; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Voraussetzungen nach Prüfungsordnung:**</td><td>**Empfohlene Voraussetzungen:**</td></tr><tr><td class="align-left" style="vertical-align: top;">keine

</td><td class="align-left" style="vertical-align: top;"></td></tr></tbody></table>

<table border="1" id="bkmrk-medienformen%3A-litera" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Medienformen:**</td><td>**Literatur:**</td></tr><tr><td class="align-left" style="vertical-align: top;"></td><td class="align-left" style="vertical-align: top;"></td></tr></tbody></table>

**Hinweise:**

# Estimation for Autonomous Mobile Robots

##### Winter 


##### (in German: Estimation for Autonomous Mobile Robots )

<table bgcolor="#7FB3D9" border="1" id="bkmrk-%5Btitle%5D" style="width: 100%; border-collapse: collapse; border-width: 1px; border-style: none;"><colgroup><col style="width: 100%;"></col></colgroup><tbody><tr style="background-color: rgb(235, 243, 249);"><td>##### <span style="color: rgb(0, 104, 180);">**Module-ID:** </span><span style="color: rgb(0, 104, 180);">**FIN-INF-120485** </span>

</td></tr></tbody></table>

<table bgcolor="#7FB3D9" border="1" id="bkmrk-" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 13.061%;"></col><col style="width: 15.442%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col></colgroup><tbody><tr><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Abbreviation**</span>

<span style="color: rgb(61, 61, 61);">AMR </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Credit Points**</span>

<span style="color: rgb(61, 61, 61);">6 </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Semester**</span>

<span style="color: rgb(61, 61, 61);">Winter </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Term**</span>

<span style="color: #3d3d3d;">starting at 1. </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);">**<span style="color: rgb(61, 61, 61);">Duration</span>**

<span style="color: rgb(61, 61, 61);">1 Semester </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Language**</span>

<span style="color: rgb(61, 61, 61);">english</span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Level**</span>

<span style="color: rgb(61, 61, 61);">Master </span>

</td></tr></tbody></table>

<table border="1" id="bkmrk-verantwortung%3A-verwe" style="border-collapse: collapse; width: 100%; height: 124.8px; border-width: 1px; border-style: none;"><colgroup><col style="width: 24.7879%;"></col><col style="width: 75.2121%;"></col></colgroup><tbody><tr style="height: 35.4px;"><td style="height: 35.4px;">**Link:**</td><td style="height: 35.4px;">[ LSF](https://lsf.ovgu.de/qislsf/rds?state=wsearchv&search=1&subdir=veranstaltung&veranstaltung.semester=20262&veranstaltung.dtxt=Estimation+for+Autonomous+Mobile+Robots&P_start=0&P_anzahl=30&P.sort=veranstaltung.dtxt&_form=display "Estimation for Autonomous Mobile Robots")</td></tr><tr><td>**Limited accessability:**</td><td>false </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Responsibility:**</td><td style="height: 29.8px;">Prof. Dr.-Ing. Benjamin Noack </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Lecturer:**</td><td style="height: 29.8px;">Prof. Dr.-Ing. Benjamin Noack </td></tr><tr><td>**Classes:**</td><td>- Lecture *Estimation for Autonomous Mobile Robots*
- Exercise *Estimation for Autonomous Mobile Robots*

 </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Applicability in curriculum:**</td><td style="height: 29.8px;">- M.Sc. INF: Informatik  
- M.Sc. INF: Informatik Wahlpflicht (SPO 2027)  
- M.Sc. INGINF: Informatik  
- M.Sc. INGINF: Ingenieurinformatik  
- M.Sc. WIF: Informatik  
- M.Sc. WIF: Informatik Wahlpflicht (SPO 2027)  
- M.Sc. DKE: Applied Data Science  
- M.Sc. DE: Methoden des Digital Engineering  
- M.Sc. DE: Methoden der Informatik  
- M.Sc. DE: Fachliche Spezialisierung  
- M.Sc. DE: Informatik Wahlpflicht (SPO 2027)  
- M.Sc. DE: Digital Engineering (SPO 2027)  
- M.Sc. DE: Engineering Specialization (SPO 2027)  
- M.Sc. VC: Computer Science  
- M.Sc. VC: Computer Science (SPO 2027)  
  
</td></tr></tbody></table>

**Intended learning outcomes:** Students who complete the course ...

- have an overview of basic problems and methods in parameter and state estimation for mobile systems.
- understand how to develop kinematic models for mobile robots and how to derive discrete-time prediction models.
- are familiar with the required mathematical tools and can derive and apply least-squares methods for localization and tracking of mobile systems, e.g., based on distance measurements.
- have a deep understanding of Kalman filtering and its nonlinear generalizations for dynamic state estimation and localization of mobile systems.

  
**Content:**

- Kinematics, System Models, and Dead Reckoning for Mobile Systems
- Sensor Models and Optimization Methods for Localization and Tracking
- DynamicState Estimation for Real-Time Localization and Tracking
- Linear Kalman Filtering and Nonlinear Generalizations

**Workload:** 56 h contact time 124 h independent study

<table border="1" id="bkmrk-studien-%2Fpr%C3%BCfungslei" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 32.0641%;"></col><col style="width: 34.9204%;"></col><col style="width: 33.0155%;"></col></colgroup><tbody><tr><td>**Pre-examination requirements:**</td><td>**Type of examination:**</td><td>**Teaching method / lecture hours per week (SWS):**</td></tr><tr><td></td><td>Oral exam (30 min)

</td><td>- Lecture (2 SWS)
- Exercise (2 SWS)

</td></tr></tbody></table>

<table border="1" id="bkmrk-voraussetzungen-nach" style="font-family: var(--font-body); font-size: 14px; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Prerequisites according to examination regulations:**</td><td>**Recommended prerequisites:**</td></tr><tr><td>none

</td><td>Linear Algebra, Analysis

</td></tr></tbody></table>

<table border="1" id="bkmrk-medienformen%3A-litera" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Media:**</td><td>**Literature:**</td></tr><tr><td></td><td>Literature will be announced in the lecture.

</td></tr></tbody></table>

**Comments:**

# Flow Visualization

##### Summer 


##### (in German: Flow Visualization )

<table bgcolor="#7FB3D9" border="1" id="bkmrk-%5Btitle%5D" style="width: 100%; border-collapse: collapse; border-width: 1px; border-style: none;"><colgroup><col style="width: 100%;"></col></colgroup><tbody><tr style="background-color: rgb(235, 243, 249);"><td>##### <span style="color: rgb(0, 104, 180);">**Module-ID:** </span><span style="color: rgb(0, 104, 180);">**FIN-INF-120261** </span>

</td></tr></tbody></table>

<table bgcolor="#7FB3D9" border="1" id="bkmrk-" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 13.061%;"></col><col style="width: 15.442%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col></colgroup><tbody><tr><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Abbreviation**</span>

<span style="color: rgb(61, 61, 61);">FlowVis </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Credit Points**</span>

<span style="color: rgb(61, 61, 61);">6 </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Semester**</span>

<span style="color: rgb(61, 61, 61);">Summer </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Term**</span>

<span style="color: #3d3d3d;">starting at 1. </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);">**<span style="color: rgb(61, 61, 61);">Duration</span>**

<span style="color: rgb(61, 61, 61);">1 Semester </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Language**</span>

<span style="color: rgb(61, 61, 61);">english</span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Level**</span>

<span style="color: rgb(61, 61, 61);">Master </span>

</td></tr></tbody></table>

<table border="1" id="bkmrk-verantwortung%3A-verwe" style="border-collapse: collapse; width: 100%; height: 124.8px; border-width: 1px; border-style: none;"><colgroup><col style="width: 24.7879%;"></col><col style="width: 75.2121%;"></col></colgroup><tbody><tr style="height: 35.4px;"><td style="height: 35.4px;">**Link:**</td><td style="height: 35.4px;">[ LSF](https://lsf.ovgu.de/qislsf/rds?state=wsearchv&search=1&subdir=veranstaltung&veranstaltung.semester=20261&veranstaltung.dtxt=Flow+Visualization&P_start=0&P_anzahl=30&P.sort=veranstaltung.dtxt&_form=display "Flow Visualization")</td></tr><tr><td>**Limited accessability:**</td><td>false </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Responsibility:**</td><td style="height: 29.8px;">Holger Theisel </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Lecturer:**</td><td style="height: 29.8px;">Holger Theisel </td></tr><tr><td>**Classes:**</td><td>- Vorlesung *Flow Visualization*
- Übung *Flow Visualization*

 </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Applicability in curriculum:**</td><td style="height: 29.8px;">- M.Sc. INF: Informatik  
- M.Sc. INGINF: Informatik  
- M.Sc. WIF: Informatik  
- M.Sc. DKE: Applied Data Science  
- M.Sc. DE: Fachliche Spezialisierung  
- M.Sc. VC: Visual Computing  
  
</td></tr></tbody></table>

**Intended learning outcomes:** The students

- understand the basic concepts of Flow Visualization in the broader context of Visualization
- are able to create their own visualization projects
- learn both the theoretical basics and applications of Flow Visualization
- are able to acquire in-depth knowledge of Flow Visualization after finishing the course

  
**Content:**

- Mathematical principles of vector and tensor fields
- Obtaining flow data
- Direct methods for flow visualization
- Texture-based methods for flow visualization
- Geometry-based methods for flow visualization
- Feature-based methods for flow visualization
- Topological methods for flow visualization
- Finite Time Lyapunov exponents
- objective methods for flow visualization

**Workload:** 56 contact hours + 124h self study

<table border="1" id="bkmrk-studien-%2Fpr%C3%BCfungslei" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 32.0641%;"></col><col style="width: 34.9204%;"></col><col style="width: 33.0155%;"></col></colgroup><tbody><tr><td>**Pre-examination requirements:**</td><td>**Type of examination:**</td><td>**Teaching method / lecture hours per week (SWS):**</td></tr><tr><td></td><td>oral exam

</td><td>- 2 SWS lecture
- 2 SWS exercise class

</td></tr></tbody></table>

<table border="1" id="bkmrk-voraussetzungen-nach" style="font-family: var(--font-body); font-size: 14px; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Prerequisites according to examination regulations:**</td><td>**Recommended prerequisites:**</td></tr><tr><td>keine

</td><td>Einführung in die Computergraphik oder Computer Graphics - an Introduction

</td></tr></tbody></table>

<table border="1" id="bkmrk-medienformen%3A-litera" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Media:**</td><td>**Literature:**</td></tr><tr><td></td><td></td></tr></tbody></table>

**Comments:**

# Human-Centred Manufacturing and Usability

##### Sommer 

#### HCAMU 

##### (in German: Human-Centred Manufacturing and Usability )

<table bgcolor="#7FB3D9" border="1" id="bkmrk-%5Btitle%5D" style="width: 100%; border-collapse: collapse; border-width: 1px; border-style: none;"><colgroup><col style="width: 100%;"></col></colgroup><tbody><tr style="background-color: rgb(235, 243, 249);"><td>##### <span style="color: rgb(0, 104, 180);">**Module-ID:** </span><span style="color: rgb(0, 104, 180);">**FIN-INF-120512** </span>

</td></tr></tbody></table>

<table bgcolor="#7FB3D9" border="1" id="bkmrk-" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 13.061%;"></col><col style="width: 15.442%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col></colgroup><tbody><tr><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Abbreviation**</span>

<span style="color: rgb(61, 61, 61);">HCMU </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Credit Points**</span>

<span style="color: rgb(61, 61, 61);">6 </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Semester**</span>

<span style="color: rgb(61, 61, 61);">Sommer </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Term**</span>

<span style="color: #3d3d3d;">2. 

</span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);">**<span style="color: rgb(61, 61, 61);">Duration</span>**

<span style="color: rgb(61, 61, 61);">1 Semester </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Language**</span>

<span style="color: rgb(61, 61, 61);">english</span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Level**</span>

<span style="color: rgb(61, 61, 61);">Master </span>

</td></tr></tbody></table>

<table border="1" id="bkmrk-verantwortung%3A-verwe" style="border-collapse: collapse; width: 100%; height: 124.8px; border-width: 1px; border-style: none;"><colgroup><col style="width: 24.7879%;"></col><col style="width: 75.2121%;"></col></colgroup><tbody><tr style="height: 35.4px;"><td style="height: 35.4px;">**Link:**</td><td style="height: 35.4px;">[ LSF](https://lsf.ovgu.de/qislsf/rds?state=wsearchv&search=1&subdir=veranstaltung&veranstaltung.semester=20261&veranstaltung.dtxt=Human-Centred+Manufacturing+and+Usability&P_start=0&P_anzahl=30&P.sort=veranstaltung.dtxt&_form=display "Human-Centred Manufacturing and Usability")</td></tr><tr><td>**Limited accessability:**</td><td></td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Responsibility:**</td><td style="height: 29.8px;">Ernesto William De Luca </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Lecturer:**</td><td style="height: 29.8px;">Marianna Ciccarelli </td></tr><tr><td>**Classes:**</td><td>Lecture/Exercise: *Human-Centred Manufacturing and Usability* </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Applicability in curriculum:**</td><td style="height: 29.8px;">- M.Sc. INF: Informatik  
- M.Sc. INGINF: Informatik  
- M.Sc. WIF: Informatik  
- M.Sc. DKE: Applied Data Science  
- M.Sc. DE: Fachliche Spezialisierung  
- M.Sc. VC: Computer Science  
  
</td></tr></tbody></table>

**Intended learning outcomes:** The students ...

- have theoretical and practical skills for the evaluation and design of safe, efficient, and human-centered work environments
- can apply principles of Human-Centered Design and Human-Centered Manufacturing
- understand risk assessment methodologies

  
**Content:** The course aims to provide both theoretical and practical skills for the evaluation and design of safe, efficient, and human-centered work environments. It will cover key concepts related to health and safety in industrial settings, with a particular focus on risk prevention and the integration of human resources into Industry 4.0 processes. Special attention will be given to the principles of Human-Centered Design and Human-Centered Manufacturing, with an introduction to occupational ergonomics and methods for analyzing physical and cognitive ergonomics. The course will also explore risk assessment methodologies, including applications in human-robot collaboration, as well as user-machine interaction paradigms and usability concepts. Learning activities are supported by hands-on exercises in ergonomic analysis and usability testing.

**Workload:**

- block course
- 40 contact hours + 140 hours self study

  
<table border="1" id="bkmrk-studien-%2Fpr%C3%BCfungslei" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 32.0641%;"></col><col style="width: 34.9204%;"></col><col style="width: 33.0155%;"></col></colgroup><tbody><tr><td>**Pre-examination requirements:**</td><td>**Type of examination:**</td><td>**Teaching method / lecture hours per week (SWS):**</td></tr><tr><td></td><td>Written report (Hausarbeit)

</td><td>4 SWS Lecture/Exercise

</td></tr></tbody></table>

<table border="1" id="bkmrk-voraussetzungen-nach" style="font-family: var(--font-body); font-size: 14px; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Prerequisites according to examination regulations:**</td><td>**Recommended prerequisites:**</td></tr><tr><td>keine

</td><td></td></tr></tbody></table>

<table border="1" id="bkmrk-medienformen%3A-litera" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Media:**</td><td>**Literature:**</td></tr><tr><td></td><td></td></tr></tbody></table>

**Comments:**

# IT-Security of Cyber-Physical Systems

**Winter**


(engl. IT-Security of Cyber-Physical Systems )

<table bgcolor="#7FB3D9" border="1" id="bkmrk-%5Btitle%5D" style="width: 100%; border-collapse: collapse; border-width: 1px; border-style: none;"><colgroup><col style="width: 100%;"></col></colgroup><tbody><tr style="background-color: rgb(235, 243, 249);"><td>##### <span style="color: rgb(0, 104, 180);">**Modulnummer: FIN-INF-120457** </span>

</td></tr></tbody></table>

<table bgcolor="#7FB3D9" border="1" id="bkmrk-" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 13.061%;"></col><col style="width: 15.442%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col></colgroup><tbody><tr><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Kürzel**</span>

<span style="color: rgb(61, 61, 61);">ITS-CPS </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**CP**</span>

<span style="color: rgb(61, 61, 61);">6 </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Semester**</span>

<span style="color: rgb(61, 61, 61);">Winter </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Fachsem.**</span>

<span style="color: #3d3d3d;">ab 1. </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);">**<span style="color: rgb(61, 61, 61);">Dauer</span>**

<span style="color: rgb(61, 61, 61);">1 Semester </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Sprache**</span>

<span style="color: rgb(61, 61, 61);">deutsch</span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Niveau**</span>

<span style="color: rgb(61, 61, 61);">Master </span>

</td></tr></tbody></table>

<table border="1" id="bkmrk-verantwortung%3A-verwe" style="border-collapse: collapse; width: 100%; height: 89.3907px; border-width: 1px; border-style: none;"><colgroup><col style="width: 20.2601%;"></col><col style="width: 79.7399%;"></col></colgroup><tbody><tr><td>**Link zum LSF:**</td><td>[ LSF](https://lsf.ovgu.de/qislsf/rds?state=wsearchv&search=1&subdir=veranstaltung&veranstaltung.semester=20262&veranstaltung.dtxt=IT-Security+of+Cyber-Physical+Systems&P_start=0&P_anzahl=30&P.sort=veranstaltung.dtxt&_form=display "IT-Security of Cyber-Physical Systems")</td></tr><tr><td>**Zugang beschränkt:**</td><td>false </td></tr><tr style="height: 29.7969px;"><td style="height: 29.7969px;">**Verantwortung:**</td><td style="height: 29.7969px;">Prof. Dr.-Ing. Jana Dittmann </td></tr><tr style="height: 29.7969px;"><td style="height: 29.7969px;">**Dozent:in:**</td><td style="height: 29.7969px;">Prof. Dr.-Ing. Jana Dittmann </td></tr><tr><td>**Lehrveranstaltungen:**</td><td>- Vorlesung *IT-Security of Cyber-Physical Systems*
- Projekt *IT-Security of Cyber-Physical Systems*

</td></tr><tr style="height: 29.7969px;"><td style="height: 29.7969px;">**Verwendbarkeit:**</td><td style="height: 29.7969px;">- M.Sc. INF: Informatik  
- M.Sc. INF: Informatik Wahlpflicht (SPO 2027)  
- M.Sc. INGINF: Informatik  
- M.Sc. WIF: Informatik  
- M.Sc. WIF: Informatik Wahlpflicht (SPO 2027)  
- M.Sc. DKE: Applied Data Science  
- M.Sc. VC: Computer Science  
- M.Sc. VC: Computer Science (SPO 2027)  
  
</td></tr></tbody></table>

**Angestrebte Lernergebnisse:** Die Studierenden

- kennen und verstehen das Zusammenspiel von System-, Netzwerk- und Anwendungssicherheit
- können IT-Sicherheit zu einer technischen Anwendung im Security-by-Design aus der Forschung selbständig bewältigen
- können bestehende Ansätze bewerten und kreativ für eine Forschungsfrage erweitern
- können sich in den technischen Anwendungsfall einarbeiten und im Team reflektieren
- können für die technische Fragestellung neue Ansätze zur IT-Sicherheit aufzeigen
- können für den Anwendungsfall die IT-Sicherheitsbedarfe feststellen und Verbesserungsalternativen vorschlagen
- können eine ausgewählte technische Lösung umsetzen, evaluieren und bewerten sowie Restrisiken aufzeigen
- können selbständig wissenschaftliche Methoden der IT-Sicherheit anwenden
- können die Ergebnisse wissenschaftlich in einem Referat präsentieren und sich einer Diskussion stellen

  
**Inhalt:** Aktuelle Herausforderungen und Erarbeitung von Lösungen zur IT Sicherheit am Beispiel von einem technischen Anwendungsfall:

- ausgewählten Grundlagen von System-, Netzwerk- und Anwendungssicherheit
- Sicherheitaspekte von Bussystemen
- Design und Realisierung hardwarenaher Sicherheitslösungen
- Bewertung sicherer Systeme mittels Evaluierung
- Wiederholung: Grundlagen der Teamarbeit, Vorlesung ist Projekt-orientiert

**Arbeitsaufwand:** Projektvorlesung zu ausgewählten technischen Themen der IT Sicherheit; Vergabe eines anspruchsvollen Themas zu selbständigen Bearbeitung und Lösung einer gestellten Aufgabe 4 SWS = 2V + 2Ü (Labor) Arbeitsaufwand: 180h (56 h Präsenzzeit + 124 h selbstständige Arbeit)

<table border="1" id="bkmrk-studien-%2Fpr%C3%BCfungslei" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 32.6591%;"></col><col style="width: 35.9941%;"></col><col style="width: 31.3468%;"></col></colgroup><tbody><tr><td>**Prüfungsvorleistungen:**</td><td>**Studien-/Prüfungsleistungen:**</td><td>**Lehrform / SWS:**</td></tr><tr><td style="vertical-align: top;">keine

</td><td class="align-left" style="vertical-align: top;">Referat mit zwei Teilleistungen (Vortrag und Ausarbeitung): Das Referat umfasst eine eigenständige und vertiefte schriftliche Auseinandersetzung mit einer Fragestellung aus dem Arbeitszusammenhang der Lehrveranstaltung unter Einbeziehung und gezielter kritischer Auswertung einschlägiger Literatur, sowie die Darstellung der eigenen Arbeit auch im Vergleich im Team und die Vermittlung sowie Bewertung der eigenen Ergebnisse im mündlichen Vortrag sowie in der anschließenden Diskussion im Team. Die Ausarbeitungen müssen schriftlich vorliegen.

</td><td class="align-left" style="vertical-align: top;">Vorlesung (2 SWS) Projekt (2 SWS)

</td></tr></tbody></table>

<table border="1" id="bkmrk-voraussetzungen-nach" style="font-family: var(--font-body); font-size: 14px; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Voraussetzungen nach Prüfungsordnung:**</td><td>**Empfohlene Voraussetzungen:**</td></tr><tr><td class="align-left" style="vertical-align: top;">keine

</td><td class="align-left" style="vertical-align: top;">Sichere Systeme, Algorithmen und Datenstrukturen, Grundlagen der Technischen Informatik

</td></tr></tbody></table>

<table border="1" id="bkmrk-medienformen%3A-litera" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Medienformen:**</td><td>**Literatur:**</td></tr><tr><td class="align-left" style="vertical-align: top;"></td><td class="align-left" style="vertical-align: top;"></td></tr></tbody></table>

**Hinweise:** [https://omen.cs.uni-magdeburg.de/itiamsl/deutsch/lehre/index.html](https://omen.cs.uni-magdeburg.de/itiamsl/deutsch/lehre/index.html)

# Introduction to Distributed Sensor Data Fusion

##### Summer 


##### (in German: Introduction to Distributed Sensor Data Fusion )

<table bgcolor="#7FB3D9" border="1" id="bkmrk-%5Btitle%5D" style="width: 100%; border-collapse: collapse; border-width: 1px; border-style: none;"><colgroup><col style="width: 100%;"></col></colgroup><tbody><tr style="background-color: rgb(235, 243, 249);"><td>##### <span style="color: rgb(0, 104, 180);">**Module-ID:** </span><span style="color: rgb(0, 104, 180);">**FIN-INF-120497** </span>

</td></tr></tbody></table>

<table bgcolor="#7FB3D9" border="1" id="bkmrk-" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 13.061%;"></col><col style="width: 15.442%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col></colgroup><tbody><tr><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Abbreviation**</span>

<span style="color: rgb(61, 61, 61);">SDF </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Credit Points**</span>

<span style="color: rgb(61, 61, 61);">6 </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Semester**</span>

<span style="color: rgb(61, 61, 61);">Summer </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Term**</span>

<span style="color: #3d3d3d;">starting at 1. </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);">**<span style="color: rgb(61, 61, 61);">Duration</span>**

<span style="color: rgb(61, 61, 61);">1 Semester </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Language**</span>

<span style="color: rgb(61, 61, 61);">english</span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Level**</span>

<span style="color: rgb(61, 61, 61);">Master </span>

</td></tr></tbody></table>

<table border="1" id="bkmrk-verantwortung%3A-verwe" style="border-collapse: collapse; width: 100%; height: 124.8px; border-width: 1px; border-style: none;"><colgroup><col style="width: 24.7879%;"></col><col style="width: 75.2121%;"></col></colgroup><tbody><tr style="height: 35.4px;"><td style="height: 35.4px;">**Link:**</td><td style="height: 35.4px;">[ LSF](https://lsf.ovgu.de/qislsf/rds?state=wsearchv&search=1&subdir=veranstaltung&veranstaltung.semester=20261&veranstaltung.dtxt=Introduction+to+Distributed+Sensor+Data+Fusion&P_start=0&P_anzahl=30&P.sort=veranstaltung.dtxt&_form=display "Introduction to Distributed Sensor Data Fusion")</td></tr><tr><td>**Limited accessability:**</td><td></td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Responsibility:**</td><td style="height: 29.8px;">Prof. Dr.-Ing. Benjamin Noack </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Lecturer:**</td><td style="height: 29.8px;">Prof. Dr.-Ing. Benjamin Noack </td></tr><tr><td>**Classes:**</td><td>- Lecture *Introduction to Distributed Sensor Data Fusion*
- Exercise *Introduction to Distributed Sensor Data Fusion*

 </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Applicability in curriculum:**</td><td style="height: 29.8px;">- M.Sc. INF: Informatik  
- M.Sc. INF: Informatik Wahlpflicht (SPO 2027)  
- M.Sc. INGINF: Informatik  
- M.Sc. INGINF: Ingenieurinformatik  
- M.Sc. WIF: Informatik  
- M.Sc. WIF: Informatik Wahlpflicht (SPO 2027)  
- M.Sc. DKE: Applied Data Science  
- M.Sc. DE: Methoden des Digital Engineering  
- M.Sc. DE: Methoden der Informatik  
- M.Sc. DE: Fachliche Spezialisierung  
- M.Sc. VC: Computer Science  
- M.Sc. VC: Computer Science (SPO 2027)  
  
</td></tr></tbody></table>

**Intended learning outcomes:** Students who complete the course ...

- have an overview of basic problems and methods in designing distributed sensor systems and their applications.
- understand how to process data in a network of sensors, what requirements the infrastructure must meet, and how to model and describe errors like measurement noise.
- are familiar with the mathematical tools and can apply them.
- can analyze, compare, and evaluate different approaches to information processing of sensor data.

  
**Content:** This lecture introduces basic principles, requirements, and methods of sensor data processing. Since data are more often gathered by networked sensor systems, this lecture places particular emphasis on distributed sensor data fusion methods. We will start by discussing the technical specifications of a sensor system and the basics of digital sensor data processing. Our study includes sampling theorems, compressive sensing, and signal matching. We will consider the required infrastructure to processing sensor data in networked systems, i.e., sensor networks. Based on this infrastructure, we can apply methods for multisensor data fusion to spatially distributed sensors and can monitor spatio-temporal processes.

**Workload:** 56 h contact time 124 h independent study

<table border="1" id="bkmrk-studien-%2Fpr%C3%BCfungslei" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 32.0641%;"></col><col style="width: 34.9204%;"></col><col style="width: 33.0155%;"></col></colgroup><tbody><tr><td>**Pre-examination requirements:**</td><td>**Type of examination:**</td><td>**Teaching method / lecture hours per week (SWS):**</td></tr><tr><td></td><td>Oral exam (30 min)

</td><td>- Lecture (2 SWS)
- Exercise (2 SWS)

</td></tr></tbody></table>

<table border="1" id="bkmrk-voraussetzungen-nach" style="font-family: var(--font-body); font-size: 14px; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Prerequisites according to examination regulations:**</td><td>**Recommended prerequisites:**</td></tr><tr><td>none

</td><td></td></tr></tbody></table>

<table border="1" id="bkmrk-medienformen%3A-litera" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Media:**</td><td>**Literature:**</td></tr><tr><td></td><td>Literature will be announced in the lecture.

</td></tr></tbody></table>

**Comments:**

# MLOps for Small Language Model Applications

##### Winter 


##### (in German: MLOps for Small Language Model Applications )

<table bgcolor="#7FB3D9" border="1" id="bkmrk-%5Btitle%5D" style="width: 100%; border-collapse: collapse; border-width: 1px; border-style: none;"><colgroup><col style="width: 100%;"></col></colgroup><tbody><tr style="background-color: rgb(235, 243, 249);"><td>##### <span style="color: rgb(0, 104, 180);">**Module-ID:** </span><span style="color: rgb(0, 104, 180);">**FIN-INF-120515** </span>

</td></tr></tbody></table>

<table bgcolor="#7FB3D9" border="1" id="bkmrk-" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 13.061%;"></col><col style="width: 15.442%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col></colgroup><tbody><tr><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Abbreviation**</span>

<span style="color: rgb(61, 61, 61);">LLMOps </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Credit Points**</span>

<span style="color: rgb(61, 61, 61);">9 </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Semester**</span>

<span style="color: rgb(61, 61, 61);">Winter </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Term**</span>

<span style="color: #3d3d3d;">starting at 1. </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);">**<span style="color: rgb(61, 61, 61);">Duration</span>**

<span style="color: rgb(61, 61, 61);">1 Semester </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Language**</span>

<span style="color: rgb(61, 61, 61);">english</span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Level**</span>

<span style="color: rgb(61, 61, 61);">Master </span>

</td></tr></tbody></table>

<table border="1" id="bkmrk-verantwortung%3A-verwe" style="border-collapse: collapse; width: 100%; height: 124.8px; border-width: 1px; border-style: none;"><colgroup><col style="width: 24.7879%;"></col><col style="width: 75.2121%;"></col></colgroup><tbody><tr style="height: 35.4px;"><td style="height: 35.4px;">**Link:**</td><td style="height: 35.4px;">[ LSF](https://lsf.ovgu.de/qislsf/rds?state=wsearchv&search=1&subdir=veranstaltung&veranstaltung.semester=20262&veranstaltung.dtxt=MLOps+for+Small+Language+Model+Applications&P_start=0&P_anzahl=30&P.sort=veranstaltung.dtxt&_form=display "MLOps for Small Language Model Applications")</td></tr><tr><td>**Limited accessability:**</td><td>true </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Responsibility:**</td><td style="height: 29.8px;">Prof. Dr. Klaus Turowski, Dr.-Ing. Abdulrahman Nahhas </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Lecturer:**</td><td style="height: 29.8px;">Prof. Dr. Klaus Turowski, Dr.-Ing. Abdulrahman Nahhas </td></tr><tr><td>**Classes:**</td><td>Vorlesung + Übung + Tutorial </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Applicability in curriculum:**</td><td style="height: 29.8px;">- M.Sc. INF: Informatik  
- M.Sc. INGINF: Informatik  
- M.Sc. WIF: Wirtschaftsinformatik  
- M.Sc. WIF: Informatik  
- M.Sc. DKE: Applied Data Science  
- M.Sc. DE: Methoden der Informatik  
- M.Sc. VC: Computer Science  
  
</td></tr></tbody></table>

**Intended learning outcomes:** Students ...

- know and understand specialized subject content that expands and deepens Large Language Models (LLM) and machine learning development and operation.
- can independently analyze problems and identify alternative solutions.
- know how to work with large language models following proper machine learning development and operation practices.
- are experienced in the theory and handling of container-based virtualization technologies such as Docker.
- know how to use higher programming languages (Python).
- know how to use various configuration and automation tools and languages to automate the development and operation of LLM solutions.
- have practical and theoretical knowledge of testing LLM-solutions, particularly in relation to essential DevOps concepts such as Continuous Integration and Continuous Delivery, LLMOps, testing, and system landscape.
- have the ability to design, create, test, commission, and support LLM solutions for business problems.

  
**Content:** The generalization and standardization of the Large Language Model Operations (LLMOps) life cycle is crucial for the effective adoption and management of Large Language Models (LLMs) in a business context. In many cases, the lifecycle of an LLM solution does not end with the delivery an initial solution; rather, subsequent model improvement, operation, monitoring, and maintenance have become essential parts of this process. At this point, sophisticated paradigms and methods are required to facilitate the continuous development and operation of these systems while preventing errors, failures, and other disruptions. The course is designed to teach the fundamentals, as well as provide initial practical experience in the development of LLM solutions and technologies, in conjunction with dedicated cloud-native technologies and an emphasis on small LLMs (SML) that are edge-suitable, may be operated on premise, or are ressource-efficient. In addition to the theoretical basics, essential concepts and technologies are discussed and applied that enable the continuous improvement, integration, delivery, and testing of LLM solutions for business problems.

**Workload:** Attendance:  
21 h lecture / 63 h exercise Independent work: 207 h

1. Preparation and follow-up of lecture &amp; exercise
2. Development of an LLM-based sotution following LLMLOps practicies to address a business problems

9 x30h (63 h attendance time + 207 h independent work)   
<table border="1" id="bkmrk-studien-%2Fpr%C3%BCfungslei" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 32.0641%;"></col><col style="width: 34.9204%;"></col><col style="width: 33.0155%;"></col></colgroup><tbody><tr><td>**Pre-examination requirements:**</td><td>**Type of examination:**</td><td>**Teaching method / lecture hours per week (SWS):**</td></tr><tr><td></td><td>Report

</td><td>Vorlesung (2 SWS) Übung (2 SWS)

</td></tr></tbody></table>

<table border="1" id="bkmrk-voraussetzungen-nach" style="font-family: var(--font-body); font-size: 14px; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Prerequisites according to examination regulations:**</td><td>**Recommended prerequisites:**</td></tr><tr><td>1. VLBA: Systemarchitectures or 2. VLBA Cloud DevOps Technologies or 3. Version control systems, DevOps practicies (CI/CD), Containerization technologies, and python.

</td><td>1. VLBA: Systemarchitectures or 2. VLBA Cloud DevOps Technologies or 3. Version control systems, DevOps practicies (CI/CD), Containerization technologies, and python.

</td></tr></tbody></table>

<table border="1" id="bkmrk-medienformen%3A-litera" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Media:**</td><td>**Literature:**</td></tr><tr><td></td><td></td></tr></tbody></table>

**Comments:**

# Management of Global Large IT-Systems in International Companies

##### Summer 


##### (in German: Management of Global Large IT-Systems in International Companies )

<table bgcolor="#7FB3D9" border="1" id="bkmrk-%5Btitle%5D" style="width: 100%; border-collapse: collapse; border-width: 1px; border-style: none;"><colgroup><col style="width: 100%;"></col></colgroup><tbody><tr style="background-color: rgb(235, 243, 249);"><td>##### <span style="color: rgb(0, 104, 180);">**Module-ID:** </span><span style="color: rgb(0, 104, 180);">**FIN-INF-120315** </span>

</td></tr></tbody></table>

<table bgcolor="#7FB3D9" border="1" id="bkmrk-" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 13.061%;"></col><col style="width: 15.442%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col></colgroup><tbody><tr><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Abbreviation**</span>

<span style="color: rgb(61, 61, 61);">MGLIIC </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Credit Points**</span>

<span style="color: rgb(61, 61, 61);">6 </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Semester**</span>

<span style="color: rgb(61, 61, 61);">Summer </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Term**</span>

<span style="color: #3d3d3d;">starting at 1. </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);">**<span style="color: rgb(61, 61, 61);">Duration</span>**

<span style="color: rgb(61, 61, 61);">1 Semester </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Language**</span>

<span style="color: rgb(61, 61, 61);">english</span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Level**</span>

<span style="color: rgb(61, 61, 61);">Master </span>

</td></tr></tbody></table>

<table border="1" id="bkmrk-verantwortung%3A-verwe" style="border-collapse: collapse; width: 100%; height: 124.8px; border-width: 1px; border-style: none;"><colgroup><col style="width: 24.7879%;"></col><col style="width: 75.2121%;"></col></colgroup><tbody><tr style="height: 35.4px;"><td style="height: 35.4px;">**Link:**</td><td style="height: 35.4px;">[ LSF](https://lsf.ovgu.de/qislsf/rds?state=wsearchv&search=1&subdir=veranstaltung&veranstaltung.semester=20261&veranstaltung.dtxt=Management+of+Global+Large+IT-Systems+in+International+Companies&P_start=0&P_anzahl=30&P.sort=veranstaltung.dtxt&_form=display "Management of Global Large IT-Systems in International Companies")</td></tr><tr><td>**Limited accessability:**</td><td></td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Responsibility:**</td><td style="height: 29.8px;">Gunter Saake </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Lecturer:**</td><td style="height: 29.8px;">Karl-Albert Bebber, Wolfgang Stockhausen </td></tr><tr><td>**Classes:**</td><td>- Block lecture *Management of Global Large IT-Systems in International Companies*
- Block Exercise class *Management of Global Large IT-Systems in International Companies*

 </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Applicability in curriculum:**</td><td style="height: 29.8px;">- M.Sc. INF: Informatik  
- M.Sc. INGINF: Informatik  
- M.Sc. WIF: Wirtschaftsinformatik  
- M.Sc. DKE: Applied Data Science  
- M.Sc. DE: Human Factors  
- M.Sc. DE: Methoden der Informatik  
- M.Sc. DE: Fachliche Spezialisierung  
- M.Sc. VC: Computer Science  
  
</td></tr></tbody></table>

**Intended learning outcomes:** Students are able to …

- understand the fundamentals of IT strategy and analyze its significance for businesses.
- describe methods for developing and implementing IT strategies.
- apply project management methodologies such as PRINCE2 and agile approaches in IT projects.
- understand multi-project management, program management and portfolio management in corporate environments.
- apply change management models such as ADKAR to manage organizational transformations.
- understand the importance of IT governance and compliance for corporate structures and regulatory requirements.
- describe stakeholder management and intercultural communication in global IT projects.
- identify risks and quality requirements in IT projects and develop appropriate control measures.
- explain data governance concepts and assess their significance for data protection, IT security, and regulatory compliance.
- describe the role of data quality, metadata management and master data management (MDM) in corporate IT.
- model, analyze, and optimize IT-supported business processes, particularly through the use of BPMN.
- understand Identity &amp; Access Management (IAM) and evaluate its implementation in enterprises.
- explain security aspects such as authentication, authorization, Single Sign-On (SSO), and two-factor authentication (2FA), as well as best practices in enterprise security management.
- assess IT security strategies and cybersecurity measures, including risk mitigation techniques.
- understand the importance of reference data management and data integration for corporate processes.
- evaluate agile methodologies such as Scrum in IT transformation projects and compare them with traditional waterfall approaches.
- understand risk and quality management processes in IT environments, including testing methodologies, compliance frameworks, and risk mitigation strategies.
- analyze and apply IT service delivery models in Shared Service Centers.

  
**Content:**

- Business Process Management and Modeling
- Process Analysis and Optimization/Standardization
- Identity and Access Management (IAM)
- Quality and Risk Management in IT Operations
- Testing and Software Quality Assurance, including Documentation
- Agile vs. Waterfall Project Management in IT
- IT Service Delivery and Shared Service Center Management
- Project and Program Management (PRINCE2 i. a.)
- Stakeholder Management in IT Projects
- Change Management (ADKAR, Organizational and Employee Transformation)
- Data Governance (Strategy, Policies, Processes and Data Quality)
- IT Strategy – Business as a Driver for IT (Balanced Scorecard)
- IT Investments and Business Decision-Making
- Insights from Ongoing IT Projects by Public Accountants and IT Project Leads from Major International Companies

**Workload:** 56 contact hours + 124 h self study

<table border="1" id="bkmrk-studien-%2Fpr%C3%BCfungslei" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 32.0641%;"></col><col style="width: 34.9204%;"></col><col style="width: 33.0155%;"></col></colgroup><tbody><tr><td>**Pre-examination requirements:**</td><td>**Type of examination:**</td><td>**Teaching method / lecture hours per week (SWS):**</td></tr><tr><td>Requirements for exam admission will be announced in the first lecture

</td><td>Written Exam (120 min)

</td><td>- 2 SWS Blockvorlesung
- 2 SWS Blockübung

</td></tr></tbody></table>

<table border="1" id="bkmrk-voraussetzungen-nach" style="font-family: var(--font-body); font-size: 14px; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Prerequisites according to examination regulations:**</td><td>**Recommended prerequisites:**</td></tr><tr><td>keine

</td><td>Knowledge about IT-Systems and Business administration

</td></tr></tbody></table>

<table border="1" id="bkmrk-medienformen%3A-litera" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Media:**</td><td>**Literature:**</td></tr><tr><td></td><td></td></tr></tbody></table>

**Comments:**

# Musik Information Retrieval

**Winter**


(engl. Music Information Retrieval )

<table bgcolor="#7FB3D9" border="1" id="bkmrk-%5Btitle%5D" style="width: 100%; border-collapse: collapse; border-width: 1px; border-style: none;"><colgroup><col style="width: 100%;"></col></colgroup><tbody><tr style="background-color: rgb(235, 243, 249);"><td>##### <span style="color: rgb(0, 104, 180);">**Modulnummer: FIN-INF-120516** </span>

</td></tr></tbody></table>

<table bgcolor="#7FB3D9" border="1" id="bkmrk-" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 13.061%;"></col><col style="width: 15.442%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col></colgroup><tbody><tr><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Kürzel**</span>

<span style="color: rgb(61, 61, 61);">MIR </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**CP**</span>

<span style="color: rgb(61, 61, 61);">6 </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Semester**</span>

<span style="color: rgb(61, 61, 61);">Winter </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Fachsem.**</span>

<span style="color: #3d3d3d;">ab 1. </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);">**<span style="color: rgb(61, 61, 61);">Dauer</span>**

<span style="color: rgb(61, 61, 61);">1 Semester </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Sprache**</span>

<span style="color: rgb(61, 61, 61);">deutsch</span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Niveau**</span>

<span style="color: rgb(61, 61, 61);">Master </span>

</td></tr></tbody></table>

<table border="1" id="bkmrk-verantwortung%3A-verwe" style="border-collapse: collapse; width: 100%; height: 89.3907px; border-width: 1px; border-style: none;"><colgroup><col style="width: 20.2601%;"></col><col style="width: 79.7399%;"></col></colgroup><tbody><tr><td>**Link zum LSF:**</td><td>[ LSF](https://lsf.ovgu.de/qislsf/rds?state=wsearchv&search=1&subdir=veranstaltung&veranstaltung.semester=20262&veranstaltung.dtxt=Musik+Information+Retrieval&P_start=0&P_anzahl=30&P.sort=veranstaltung.dtxt&_form=display "Musik Information Retrieval")</td></tr><tr><td>**Zugang beschränkt:**</td><td></td></tr><tr style="height: 29.7969px;"><td style="height: 29.7969px;">**Verantwortung:**</td><td style="height: 29.7969px;">Sebastian Stober </td></tr><tr style="height: 29.7969px;"><td style="height: 29.7969px;">**Dozent:in:**</td><td style="height: 29.7969px;">Sebastian Stober </td></tr><tr><td>**Lehrveranstaltungen:**</td><td>- Vorlesung *Musik Information Retrieval*
- Übung *Musik Information Retrieval*

</td></tr><tr style="height: 29.7969px;"><td style="height: 29.7969px;">**Verwendbarkeit:**</td><td style="height: 29.7969px;">- M.Sc. INF: Informatik  
- M.Sc. INGINF: Informatik  
- M.Sc. WIF: Informatik  
- M.Sc. DKE: Applied Data Science  
- M.Sc. DE: Methoden der Informatik  
- M.Sc. VC: Computer Science  
  
</td></tr></tbody></table>

**Angestrebte Lernergebnisse:** Die Studierenden ...

- kennen die Grundlagen der digitalen Musikverarbeitung
- kennen unterschiedliche Musikformate (Repräsentationen) und relevanter Merkmale
- können Probleme der Musikanalyse mit Hilfe von Theorien und Methoden der Informatik analysieren und modellieren
- können computergestützte Lösungen für die Analyse von Musikdaten umzusetzen und erproben (u.a. Musiksynchronisation, Strukturanalyse, Content-Based Retrieval, Quellentrennung)

  
**Inhalt:**

- Music Representations
- Fourier Analysis of Signals
- Music Synchronization
- Music Structure Analysis
- Chord Recognition
- Tempo and Beat Tracking
- Content-Based Audio Retrieval
- Musically Informed Audio Decomposition

**Arbeitsaufwand:**

- Präsenzzeit = 56 Stunden
- Selbstständige Arbeit = 124 Stunden: Vor- und Nachbearbeitung von Vorlesung und Übung, Bearbeiten von Übungs- und Programmieraufgaben, Kursprojekt

  
<table border="1" id="bkmrk-studien-%2Fpr%C3%BCfungslei" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 32.6591%;"></col><col style="width: 35.9941%;"></col><col style="width: 31.3468%;"></col></colgroup><tbody><tr><td>**Prüfungsvorleistungen:**</td><td>**Studien-/Prüfungsleistungen:**</td><td>**Lehrform / SWS:**</td></tr><tr><td style="vertical-align: top;"></td><td class="align-left" style="vertical-align: top;">Prüfung in mündlicher Form: Ankündigung der notwendigen Vorleistungen in der ersten Veranstaltungswoche und auf der Vorlesungswebseite; Schein (mündlich): Ankündigung der notwendigen Vorleistungen in der ersten Veranstaltungswoche und auf der Vorlesungswebseite

</td><td class="align-left" style="vertical-align: top;">- Vorlesung (2 SWS)
- Übung (2 SWS)

  
</td></tr></tbody></table>

<table border="1" id="bkmrk-voraussetzungen-nach" style="font-family: var(--font-body); font-size: 14px; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Voraussetzungen nach Prüfungsordnung:**</td><td>**Empfohlene Voraussetzungen:**</td></tr><tr><td class="align-left" style="vertical-align: top;">keine

</td><td class="align-left" style="vertical-align: top;"></td></tr></tbody></table>

<table border="1" id="bkmrk-medienformen%3A-litera" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Medienformen:**</td><td>**Literatur:**</td></tr><tr><td class="align-left" style="vertical-align: top;"></td><td class="align-left" style="vertical-align: top;">Meinard Müller: Fundamentals of Music Processing Using Python and Jupyter Notebooks 2nd edition, Springer 2021 ISBN: 978-3-030-69807-2

</td></tr></tbody></table>

**Hinweise:**

# Narrative Visualization

##### Summer 


##### (in German: Narrative Visualization )

<table bgcolor="#7FB3D9" border="1" id="bkmrk-%5Btitle%5D" style="width: 100%; border-collapse: collapse; border-width: 1px; border-style: none;"><colgroup><col style="width: 100%;"></col></colgroup><tbody><tr style="background-color: rgb(235, 243, 249);"><td>##### <span style="color: rgb(0, 104, 180);">**Module-ID:** </span><span style="color: rgb(0, 104, 180);">**FIN-INF-120523** </span>

</td></tr></tbody></table>

<table bgcolor="#7FB3D9" border="1" id="bkmrk-" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 13.061%;"></col><col style="width: 15.442%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col></colgroup><tbody><tr><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Abbreviation**</span>

<span style="color: rgb(61, 61, 61);">NarVis </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Credit Points**</span>

<span style="color: rgb(61, 61, 61);">3 </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Semester**</span>

<span style="color: rgb(61, 61, 61);">Summer </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Term**</span>

<span style="color: #3d3d3d;">starting at 1. </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);">**<span style="color: rgb(61, 61, 61);">Duration</span>**

<span style="color: rgb(61, 61, 61);">1 Semester </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Language**</span>

<span style="color: rgb(61, 61, 61);">english</span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Level**</span>

<span style="color: rgb(61, 61, 61);">Master </span>

</td></tr></tbody></table>

<table border="1" id="bkmrk-verantwortung%3A-verwe" style="border-collapse: collapse; width: 100%; height: 124.8px; border-width: 1px; border-style: none;"><colgroup><col style="width: 24.7879%;"></col><col style="width: 75.2121%;"></col></colgroup><tbody><tr style="height: 35.4px;"><td style="height: 35.4px;">**Link:**</td><td style="height: 35.4px;">[ LSF](https://lsf.ovgu.de/qislsf/rds?state=wsearchv&search=1&subdir=veranstaltung&veranstaltung.semester=20261&veranstaltung.dtxt=Narrative+Visualization&P_start=0&P_anzahl=30&P.sort=veranstaltung.dtxt&_form=display "Narrative Visualization")</td></tr><tr><td>**Limited accessability:**</td><td>true </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Responsibility:**</td><td style="height: 29.8px;">Bernhard Preim </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Lecturer:**</td><td style="height: 29.8px;">Bernhard Preim </td></tr><tr><td>**Classes:**</td><td>Seminar *Narrative Visualization* </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Applicability in curriculum:**</td><td style="height: 29.8px;">- M.Sc. INF: Informatik  
- M.Sc. INGINF: Informatik  
- M.Sc. WIF: Informatik  
- M.Sc. DKE: Applied Data Science  
- M.Sc. DE: Human Factors  
- M.Sc. DE: Fachliche Spezialisierung  
- M.Sc. VC: Visual Computing  
  
</td></tr></tbody></table>

**Intended learning outcomes:** Students ...

- can apply methods of narrative visualization for Science communication
- can design and present topics of Science communication

  
**Content:**

- Overview of Narrative Visualization
- Concepts and Tools for Story Generation
- Applications in climate research, molecular research and astronomy
- Applications in business and finance

**Workload:** 28 h contact hours + 152 h self study

<table border="1" id="bkmrk-studien-%2Fpr%C3%BCfungslei" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 32.0641%;"></col><col style="width: 34.9204%;"></col><col style="width: 33.0155%;"></col></colgroup><tbody><tr><td>**Pre-examination requirements:**</td><td>**Type of examination:**</td><td>**Teaching method / lecture hours per week (SWS):**</td></tr><tr><td></td><td>Referat

</td><td>2 SWS Seminar

</td></tr></tbody></table>

<table border="1" id="bkmrk-voraussetzungen-nach" style="font-family: var(--font-body); font-size: 14px; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Prerequisites according to examination regulations:**</td><td>**Recommended prerequisites:**</td></tr><tr><td>keine

</td><td>Module *Visualization*

</td></tr></tbody></table>

<table border="1" id="bkmrk-medienformen%3A-litera" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Media:**</td><td>**Literature:**</td></tr><tr><td></td><td></td></tr></tbody></table>

**Comments:**

# Praktikum IT Sicherheit

**jedes**


(engl. Praktikum IT-Security )

<table bgcolor="#7FB3D9" border="1" id="bkmrk-%5Btitle%5D" style="width: 100%; border-collapse: collapse; border-width: 1px; border-style: none;"><colgroup><col style="width: 100%;"></col></colgroup><tbody><tr style="background-color: rgb(235, 243, 249);"><td>##### <span style="color: rgb(0, 104, 180);">**Modulnummer: FIN-INF-120291** </span>

</td></tr></tbody></table>

<table bgcolor="#7FB3D9" border="1" id="bkmrk-" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 13.061%;"></col><col style="width: 15.442%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col></colgroup><tbody><tr><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Kürzel**</span>

<span style="color: rgb(61, 61, 61);">P-ITSEC </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**CP**</span>

<span style="color: rgb(61, 61, 61);">6 </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Semester**</span>

<span style="color: rgb(61, 61, 61);">jedes </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Fachsem.**</span>

<span style="color: #3d3d3d;">ab 1. </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);">**<span style="color: rgb(61, 61, 61);">Dauer</span>**

<span style="color: rgb(61, 61, 61);">1 Semester </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Sprache**</span>

<span style="color: rgb(61, 61, 61);">deutsch</span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Niveau**</span>

<span style="color: rgb(61, 61, 61);">Master </span>

</td></tr></tbody></table>

<table border="1" id="bkmrk-verantwortung%3A-verwe" style="border-collapse: collapse; width: 100%; height: 89.3907px; border-width: 1px; border-style: none;"><colgroup><col style="width: 20.2601%;"></col><col style="width: 79.7399%;"></col></colgroup><tbody><tr><td>**Link zum LSF:**</td><td>[ LSF](https://lsf.ovgu.de/qislsf/rds?state=wsearchv&search=1&subdir=veranstaltung&veranstaltung.semester=20261&veranstaltung.dtxt=Praktikum+IT+Sicherheit&P_start=0&P_anzahl=30&P.sort=veranstaltung.dtxt&_form=display "Praktikum IT Sicherheit")</td></tr><tr><td>**Zugang beschränkt:**</td><td>false </td></tr><tr style="height: 29.7969px;"><td style="height: 29.7969px;">**Verantwortung:**</td><td style="height: 29.7969px;">Prof. Dr.-Ing. Jana Dittmann </td></tr><tr style="height: 29.7969px;"><td style="height: 29.7969px;">**Dozent:in:**</td><td style="height: 29.7969px;">PD Dr.-Ing. habil. Christian Krätzer </td></tr><tr><td>**Lehrveranstaltungen:**</td><td>Wissenschaftliches Projekt *Praktikum IT-Sicherheit*</td></tr><tr style="height: 29.7969px;"><td style="height: 29.7969px;">**Verwendbarkeit:**</td><td style="height: 29.7969px;">- M.Sc. INF: Informatik  
- M.Sc. INF: Informatik Wahlpflicht (SPO 2027)  
- M.Sc. INGINF: Informatik  
- M.Sc. WIF: Informatik  
- M.Sc. WIF: Informatik Wahlpflicht (SPO 2027)  
- M.Sc. DKE: Applied Data Science  
- M.Sc. DE: Methoden der Informatik  
- M.Sc. DE: Interdisziplinäres Team-Projekt  
- M.Sc. DE: Digital Engineering-Projekt  
- M.Sc. VC: Computer Science  
- M.Sc. VC: Computer Science (SPO 2027)  
  
</td></tr></tbody></table>

**Angestrebte Lernergebnisse:** Die Studierenden ...

- kennen und verstehen Sicherheitsaspekte des ausgewählten Themas
- können die ausgewählte Forschungsfragen selbständig bewältigen
- können bestehende Ansätze bewerten und kreativ für eine Forschungsfrage erweitern
- können sich in Sicherheitsaspekte des ausgewählten Themas einarbeiten und reflektieren
- können für die Fragestellung neue Ansätze für das ausgewählten Thema aufzeigen
- können für das ausgewählte Thema Sicherheitsbedarfe feststellen und Verbesserungsalternativen vorschlagen
- können eine ausgewählte Lösung umsetzen, evaluieren und bewerten sowie Restrisiken aufzeigen
- können selbständig wissenschaftliche Methoden der IT-Sicherheit anwenden
- können die Ergebnisse wissenschaftlich in einem Referat präsentieren und sich einer Diskussion stellen
- können Herausforderungen allein oder ggf. in der Teamarbeit erkennen und reflektieren sowie angehen

  
**Inhalt:** Praktikum als Wissenschaftliches Projekt mit Erarbeitung eines Demonstrators als Einzel- oder Teamprojekt:

- Bearbeitung eines ausgewählten, aktuellen Themas zur Cybersicherheit
- Lösung einer Forschungsaufgabe wie zum Beispiel aus: 
    - System-, Netzwerk- und Anwendungssicherheit Kryptologie
    - Protokolle Mediensicherheit und
    - Biometrische Systeme
    - Spezifikation und formale Verifikation sicherer Systeme
    - IT Sicherheitsmanagement

**Arbeitsaufwand:**

- 28 h Präsenzzeit (Projektbesprechung, Abgabe und Abnahme)
- 152 h selbstständige Arbeit (132 h Entwicklung einer Softwarelösung 20 h Vorbereitung und Durchführung einer Präsentation und der Abgabe der Ergebnisse)

  
<table border="1" id="bkmrk-studien-%2Fpr%C3%BCfungslei" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 32.6591%;"></col><col style="width: 35.9941%;"></col><col style="width: 31.3468%;"></col></colgroup><tbody><tr><td>**Prüfungsvorleistungen:**</td><td>**Studien-/Prüfungsleistungen:**</td><td>**Lehrform / SWS:**</td></tr><tr><td style="vertical-align: top;">keine

</td><td class="align-left" style="vertical-align: top;">Hausarbeit (Beschreibung der erarbeiteten Lösung und der zugehörigen Evaluationsergebnisse)

</td><td class="align-left" style="vertical-align: top;">Wissenschaftliches Projekt (2 SWS)

</td></tr></tbody></table>

<table border="1" id="bkmrk-voraussetzungen-nach" style="font-family: var(--font-body); font-size: 14px; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Voraussetzungen nach Prüfungsordnung:**</td><td>**Empfohlene Voraussetzungen:**</td></tr><tr><td class="align-left" style="vertical-align: top;">keine

</td><td class="align-left" style="vertical-align: top;"></td></tr></tbody></table>

<table border="1" id="bkmrk-medienformen%3A-litera" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Medienformen:**</td><td>**Literatur:**</td></tr><tr><td class="align-left" style="vertical-align: top;"></td><td class="align-left" style="vertical-align: top;"></td></tr></tbody></table>

**Hinweise:** [https://omen.cs.uni-magdeburg.de/itiamsl/deutsch/lehre/index.html](https://omen.cs.uni-magdeburg.de/itiamsl/deutsch/lehre/index.html)

# Recent Topics in Business Informatics

##### every 


##### (in German: Recent Topics in Business Informatics )

<table bgcolor="#7FB3D9" border="1" id="bkmrk-%5Btitle%5D" style="width: 100%; border-collapse: collapse; border-width: 1px; border-style: none;"><colgroup><col style="width: 100%;"></col></colgroup><tbody><tr style="background-color: rgb(235, 243, 249);"><td>##### <span style="color: rgb(0, 104, 180);">**Module-ID:** </span><span style="color: rgb(0, 104, 180);">**FIN-INF-120318** </span>

</td></tr></tbody></table>

<table bgcolor="#7FB3D9" border="1" id="bkmrk-" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 13.061%;"></col><col style="width: 15.442%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col></colgroup><tbody><tr><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Abbreviation**</span>

<span style="color: rgb(61, 61, 61);">RTBI </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Credit Points**</span>

<span style="color: rgb(61, 61, 61);">6 </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Semester**</span>

<span style="color: rgb(61, 61, 61);">every </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Term**</span>

<span style="color: #3d3d3d;">2. 

</span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);">**<span style="color: rgb(61, 61, 61);">Duration</span>**

<span style="color: rgb(61, 61, 61);">1 Semester </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Language**</span>

<span style="color: rgb(61, 61, 61);">english</span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Level**</span>

<span style="color: rgb(61, 61, 61);">Master </span>

</td></tr></tbody></table>

<table border="1" id="bkmrk-verantwortung%3A-verwe" style="border-collapse: collapse; width: 100%; height: 124.8px; border-width: 1px; border-style: none;"><colgroup><col style="width: 24.7879%;"></col><col style="width: 75.2121%;"></col></colgroup><tbody><tr style="height: 35.4px;"><td style="height: 35.4px;">**Link:**</td><td style="height: 35.4px;">[ LSF](https://lsf.ovgu.de/qislsf/rds?state=wsearchv&search=1&subdir=veranstaltung&veranstaltung.semester=20261&veranstaltung.dtxt=Recent+Topics+in+Business+Informatics&P_start=0&P_anzahl=30&P.sort=veranstaltung.dtxt&_form=display "Recent Topics in Business Informatics")</td></tr><tr><td>**Limited accessability:**</td><td>false </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Responsibility:**</td><td style="height: 29.8px;">Prof. Dr. Klaus Turowski </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Lecturer:**</td><td style="height: 29.8px;">Dr. Daniel Staegemann , Abdulrahman Nahhas </td></tr><tr><td>**Classes:**</td><td>Seminar *RTBI* </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Applicability in curriculum:**</td><td style="height: 29.8px;">- M.Sc. INF: Informatik  
- M.Sc. INF: Schlüssel- und Methodenkompetenzen  
- M.Sc. INGINF: Informatik  
- M.Sc. WIF: Wirtschaftsinformatik  
- M.Sc. WIF: Schlüssel- und Methodenkompetenzen  
- M.Sc. DKE: Applied Data Science  
- M.Sc. DE: Human Factors  
- M.Sc. DE: Methoden der Informatik  
- M.Sc. DE: Fachliche Spezialisierung  
- M.Sc. VC: Computer Science  
  
</td></tr></tbody></table>

**Intended learning outcomes:** Students ...

- can acquire new knowledge independently through self-sufficient research and consultation of thematically relevant scientific literature and make it usable for themselves.
- can write a scientific paper almost independently and with only a small amount of support and present the final result.
- can convey knowledge from a subject area of their choice as part of a specialist presentation, explain the research results they have achieved and defend the arguments they have put forward in a scientific discussion.
- know the steps involved in writing a scientific paper, from finding a specific topic to presenting it at a conference.
- have carried out the necessary steps for crafting a scientific publication themselves and have developed an understanding of them.

  
**Content:**

- Research, Literature Search, Citation &amp; Plagiarism
- Scientific methods
- Hands-On-Guidance
- Introduction to selected Business Informatics topics

**Workload:** presence = 40 hr.:

```
40 h lecture with integrated exercise

```

independent work = 140 hr: ```
Follow-up of the lecture, write paper and review, and present paper.

```

  
<table border="1" id="bkmrk-studien-%2Fpr%C3%BCfungslei" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 32.0641%;"></col><col style="width: 34.9204%;"></col><col style="width: 33.0155%;"></col></colgroup><tbody><tr><td>**Pre-examination requirements:**</td><td>**Type of examination:**</td><td>**Teaching method / lecture hours per week (SWS):**</td></tr><tr><td></td><td>Referat

</td><td>Seminar (4SWS)

</td></tr></tbody></table>

<table border="1" id="bkmrk-voraussetzungen-nach" style="font-family: var(--font-body); font-size: 14px; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Prerequisites according to examination regulations:**</td><td>**Recommended prerequisites:**</td></tr><tr><td>none

</td><td>Basics of scientific writing

</td></tr></tbody></table>

<table border="1" id="bkmrk-medienformen%3A-litera" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Media:**</td><td>**Literature:**</td></tr><tr><td></td><td></td></tr></tbody></table>

**Comments:**

# Scientific Project on Databases for Multi-Dimensional Data, Genomics, and modern Hardware

##### every 


##### (in German: Scientific Project on Databases for Multi-Dimensional Data, Genomics, and modern Hardware )

<table bgcolor="#7FB3D9" border="1" id="bkmrk-%5Btitle%5D" style="width: 100%; border-collapse: collapse; border-width: 1px; border-style: none;"><colgroup><col style="width: 100%;"></col></colgroup><tbody><tr style="background-color: rgb(235, 243, 249);"><td>##### <span style="color: rgb(0, 104, 180);">**Module-ID:** </span><span style="color: rgb(0, 104, 180);">**FIN-INF-120507** </span>

</td></tr></tbody></table>

<table bgcolor="#7FB3D9" border="1" id="bkmrk-" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 13.061%;"></col><col style="width: 15.442%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col></colgroup><tbody><tr><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Abbreviation**</span>

<span style="color: rgb(61, 61, 61);">SPDB </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Credit Points**</span>

<span style="color: rgb(61, 61, 61);">6 </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Semester**</span>

<span style="color: rgb(61, 61, 61);">every </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Term**</span>

<span style="color: #3d3d3d;">starting at 1. </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);">**<span style="color: rgb(61, 61, 61);">Duration</span>**

<span style="color: rgb(61, 61, 61);">1 Semester </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Language**</span>

<span style="color: rgb(61, 61, 61);">english</span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Level**</span>

<span style="color: rgb(61, 61, 61);">Master </span>

</td></tr></tbody></table>

<table border="1" id="bkmrk-verantwortung%3A-verwe" style="border-collapse: collapse; width: 100%; height: 124.8px; border-width: 1px; border-style: none;"><colgroup><col style="width: 24.7879%;"></col><col style="width: 75.2121%;"></col></colgroup><tbody><tr style="height: 35.4px;"><td style="height: 35.4px;">**Link:**</td><td style="height: 35.4px;">[ LSF](https://lsf.ovgu.de/qislsf/rds?state=wsearchv&search=1&subdir=veranstaltung&veranstaltung.semester=20261&veranstaltung.dtxt=Scientific+Project+on+Databases+for+Multi-Dimensional+Data,+Genomics,+and+modern+Hardware&P_start=0&P_anzahl=30&P.sort=veranstaltung.dtxt&_form=display "Scientific Project on Databases for Multi-Dimensional Data, Genomics, and modern Hardware")</td></tr><tr><td>**Limited accessability:**</td><td>true </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Responsibility:**</td><td style="height: 29.8px;">Gunter Saake </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Lecturer:**</td><td style="height: 29.8px;">Gunter Saake </td></tr><tr><td>**Classes:**</td><td>Lecture *Scientific Project on Databases for Multi-Dimensional Data, Genomics, and modern Hardware* </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Applicability in curriculum:**</td><td style="height: 29.8px;">- M.Sc. INF: Schlüssel- und Methodenkompetenzen  
- M.Sc. INGINF: Schlüssel- und Methodenkompetenzen  
- M.Sc. WIF: Schlüssel- und Methodenkompetenzen  
- M.Sc. DKE: Applied Data Science  
- M.Sc. DE: Interdisziplinäres Team-Projekt  
- M.Sc. DE: Fachliche Spezialisierung  
  
</td></tr></tbody></table>

**Intended learning outcomes:** The students ...

- work and coordinate in a team
- write academic papers
- present scientific results
- acquire knowledge of an advanced research topic on their own
- self-sufficiently develop solutions on selected topics of databases or their applications
- assess their own work critically

  
**Content:**

- Scientific writing
- Survey of research literature
- Advanced research topics in the area of databases, genomics and modern hardware

**Workload:** contact hours: 14h lectures + 8h presentations + 14h consultations  
self study: 60h implementation + 24h presentations + 30h papers

<table border="1" id="bkmrk-studien-%2Fpr%C3%BCfungslei" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 32.0641%;"></col><col style="width: 34.9204%;"></col><col style="width: 33.0155%;"></col></colgroup><tbody><tr><td>**Pre-examination requirements:**</td><td>**Type of examination:**</td><td>**Teaching method / lecture hours per week (SWS):**</td></tr><tr><td></td><td>Seminar paper (Referat)

</td><td>- Lecture (2 SWS)
- Supervision (2 SWS)

</td></tr></tbody></table>

<table border="1" id="bkmrk-voraussetzungen-nach" style="font-family: var(--font-body); font-size: 14px; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Prerequisites according to examination regulations:**</td><td>**Recommended prerequisites:**</td></tr><tr><td>none

</td><td>Programming Knowledge in C++, Python, Java or Rust

</td></tr></tbody></table>

<table border="1" id="bkmrk-medienformen%3A-litera" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Media:**</td><td>**Literature:**</td></tr><tr><td></td><td></td></tr></tbody></table>

**Comments:** Requirement: Passing an initial programming test

# Scientific Writing

##### Winter 


##### (in German: Scientific Writing )

<table bgcolor="#7FB3D9" border="1" id="bkmrk-%5Btitle%5D" style="width: 100%; border-collapse: collapse; border-width: 1px; border-style: none;"><colgroup><col style="width: 100%;"></col></colgroup><tbody><tr style="background-color: rgb(235, 243, 249);"><td>##### <span style="color: rgb(0, 104, 180);">**Module-ID:** </span><span style="color: rgb(0, 104, 180);">**FIN-INF-120511** </span>

</td></tr></tbody></table>

<table bgcolor="#7FB3D9" border="1" id="bkmrk-" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 13.061%;"></col><col style="width: 15.442%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col></colgroup><tbody><tr><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Abbreviation**</span>

<span style="color: rgb(61, 61, 61);">SciWri </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Credit Points**</span>

<span style="color: rgb(61, 61, 61);">6 </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Semester**</span>

<span style="color: rgb(61, 61, 61);">Winter </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Term**</span>

<span style="color: #3d3d3d;">starting at 1. </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);">**<span style="color: rgb(61, 61, 61);">Duration</span>**

<span style="color: rgb(61, 61, 61);">1 Semester </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Language**</span>

<span style="color: rgb(61, 61, 61);">english</span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Level**</span>

<span style="color: rgb(61, 61, 61);">Master </span>

</td></tr></tbody></table>

<table border="1" id="bkmrk-verantwortung%3A-verwe" style="border-collapse: collapse; width: 100%; height: 124.8px; border-width: 1px; border-style: none;"><colgroup><col style="width: 24.7879%;"></col><col style="width: 75.2121%;"></col></colgroup><tbody><tr style="height: 35.4px;"><td style="height: 35.4px;">**Link:**</td><td style="height: 35.4px;">[ LSF](https://lsf.ovgu.de/qislsf/rds?state=wsearchv&search=1&subdir=veranstaltung&veranstaltung.semester=20262&veranstaltung.dtxt=Scientific+Writing&P_start=0&P_anzahl=30&P.sort=veranstaltung.dtxt&_form=display "Scientific Writing")</td></tr><tr><td>**Limited accessability:**</td><td>true </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Responsibility:**</td><td style="height: 29.8px;">PD Dr. Claudia Krull </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Lecturer:**</td><td style="height: 29.8px;">Temitope Ibidunni Akinloye </td></tr><tr><td>**Classes:**</td><td>Seminar *Scientific Writing* </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Applicability in curriculum:**</td><td style="height: 29.8px;">- M.Sc. INF: Schlüssel- und Methodenkompetenzen  
- M.Sc. INF: Schlüssel- und Methodenkompetenz (SPO 2027)  
- M.Sc. INGINF: Schlüssel- und Methodenkompetenzen  
- M.Sc. WIF: Schlüssel- und Methodenkompetenzen  
- M.Sc. WIF: Schlüssel- und Methodenkompetenz (SPO 2027)  
- M.Sc. DKE: Applied Data Science  
- M.Sc. DE: Human Factors  
- M.Sc. DE: Fachliche Spezialisierung  
- M.Sc. DE: Schlüssel- und Methodenkompetenz (SPO 2027)  
- M.Sc. VC: Schlüssel- und Methodenkompetenzen  
- M.Sc. VC: Schlüssel- und Methodenkompetenz (SPO 2027)  
  
</td></tr></tbody></table>

**Intended learning outcomes:**

- Students are able to conduct a literature research in order to gain an overview of an area of interest.
- Students can identify open research questions based on a literature research.
- Students are able to identify and formulate research hypothesis
- Students understand how a scientific publication is structured, can read it and extract the important information.
- Students are able to write a research proposal on a selected topic in the form of a scientific publication.
- Students are able to identify and select possible solution methods for a scientific question.
- Students are able to prepare a presentation to explain and defend their research proposal.
- Students understand how to present a research topic proposal on a selected topic.
- Students are able to evaluate the quality of others scientific work

  
**Content:**

- Literature citation and paraphrasing
- Presentations Review scientific articles
- Argument formation
- Knowledge and application of academic writing styles
- Peer review assessment

**Workload:**

- 28h Seminar
- 152h independent work

  
<table border="1" id="bkmrk-studien-%2Fpr%C3%BCfungslei" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 32.0641%;"></col><col style="width: 34.9204%;"></col><col style="width: 33.0155%;"></col></colgroup><tbody><tr><td>**Pre-examination requirements:**</td><td>**Type of examination:**</td><td>**Teaching method / lecture hours per week (SWS):**</td></tr><tr><td>participation in all classes  
completion of assignments  
keeping all deadlines

</td><td>Seminar paper (Paper + Reviews) Presentation

</td><td>Seminar (2 SWS)

</td></tr></tbody></table>

<table border="1" id="bkmrk-voraussetzungen-nach" style="font-family: var(--font-body); font-size: 14px; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Prerequisites according to examination regulations:**</td><td>**Recommended prerequisites:**</td></tr><tr><td>keine

</td><td></td></tr></tbody></table>

<table border="1" id="bkmrk-medienformen%3A-litera" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Media:**</td><td>**Literature:**</td></tr><tr><td></td><td></td></tr></tbody></table>

**Comments:** participation is limited to 40

# Scrum-in-Practice

**Winter**


(engl. Scrum-in-Practice )

<table bgcolor="#7FB3D9" border="1" id="bkmrk-%5Btitle%5D" style="width: 100%; border-collapse: collapse; border-width: 1px; border-style: none;"><colgroup><col style="width: 100%;"></col></colgroup><tbody><tr style="background-color: rgb(235, 243, 249);"><td>##### <span style="color: rgb(0, 104, 180);">**Modulnummer: FIN-INF-120438** </span>

</td></tr></tbody></table>

<table bgcolor="#7FB3D9" border="1" id="bkmrk-" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 13.061%;"></col><col style="width: 15.442%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col></colgroup><tbody><tr><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Kürzel**</span>

<span style="color: rgb(61, 61, 61);">SIP </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**CP**</span>

<span style="color: rgb(61, 61, 61);">6 </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Semester**</span>

<span style="color: rgb(61, 61, 61);">Winter </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Fachsem.**</span>

<span style="color: #3d3d3d;">ab 1. </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);">**<span style="color: rgb(61, 61, 61);">Dauer</span>**

<span style="color: rgb(61, 61, 61);">1 Semester </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Sprache**</span>

<span style="color: rgb(61, 61, 61);">deutsch</span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Niveau**</span>

<span style="color: rgb(61, 61, 61);">Master </span>

</td></tr></tbody></table>

<table border="1" id="bkmrk-verantwortung%3A-verwe" style="border-collapse: collapse; width: 100%; height: 89.3907px; border-width: 1px; border-style: none;"><colgroup><col style="width: 20.2601%;"></col><col style="width: 79.7399%;"></col></colgroup><tbody><tr><td>**Link zum LSF:**</td><td>[ LSF](https://lsf.ovgu.de/qislsf/rds?state=wsearchv&search=1&subdir=veranstaltung&veranstaltung.semester=20262&veranstaltung.dtxt=Scrum-in-Practice&P_start=0&P_anzahl=30&P.sort=veranstaltung.dtxt&_form=display "Scrum-in-Practice")</td></tr><tr><td>**Zugang beschränkt:**</td><td>true </td></tr><tr style="height: 29.7969px;"><td style="height: 29.7969px;">**Verantwortung:**</td><td style="height: 29.7969px;">Prof. Dr. Frank Ortmeier </td></tr><tr style="height: 29.7969px;"><td style="height: 29.7969px;">**Dozent:in:**</td><td style="height: 29.7969px;">Prof. Dr. Frank Ortmeier </td></tr><tr><td>**Lehrveranstaltungen:**</td><td>- Vorlesung *Scrum-in-Practice*
- Übung *Scrum-in-Practice*

Die Lehrveranstaltungen finden zum Teil im Blockformat statt. </td></tr><tr style="height: 29.7969px;"><td style="height: 29.7969px;">**Verwendbarkeit:**</td><td style="height: 29.7969px;">- M.Sc. INF: Informatik  
- M.Sc. INF: Schlüssel- und Methodenkompetenzen  
- M.Sc. INGINF: Informatik  
- M.Sc. INGINF: Schlüssel- und Methodenkompetenzen  
- M.Sc. DKE: Applied Data Science  
- M.Sc. DE: Methoden der Informatik  
- M.Sc. DE: Fachliche Spezialisierung  
- M.Sc. VC: Computer Science  
- M.Sc. VC: Schlüssel- und Methodenkompetenzen  
  
</td></tr></tbody></table>

**Angestrebte Lernergebnisse:** Die Studierenden ...

- kennen die Projektmanagementmethode Scrum
- wenden agile Softwareentwicklungsmethoden praktisch an
- gewinnen praktische Erfahrungen mittels Durchführung eines Projektes
- reflektieren ihr Selbst- und Projektmanagement

  
**Inhalt:**

- In diesem Modul werden theoretische Kenntnisse und praktische Kompetenzen im Umgang mit Scrum vermittelt.
- Die Veranstaltung besteht aus drei Teilen.
- In einem Einführungsteil werden in zwei Vorlesungen die notwendigen Konzepte des Scrum-ProzessModells vorgestellt und die zur erfolgreichen Projektdurchführung notwendigen Technologien aufgelistet.
- Im Hauptteil der Veranstaltung wird in einer 1-wöchigen Blockveranstaltung ein Projekt mittels Scrum umgesetzt. Diese erfolgt in Projektteams von 4-5 Teilnehmern.
- Während dieser Phase finden 2mal täglich Scrum-Meetings mit den Betreuern statt. Als Ergebnis lernen die Teilnehmer zielgerichtet und effizient nach diesem Entwicklungsmodell zu entwickeln.
- Die Blockveranstaltung findet in einer Woche während der Vorlesungsfreien Zeit. Hier besteht natürlich Anwesenheitspflicht.
- Zur erfolgreichen Durchführung in der Projektarbeit wird von jedem Teilnehmer ein sorgfältiges Einarbeiten in die notwendigen Technologien erwartet.
- Nach Abschluss der Projektwoche reflektieren die Teilnehmer Ihre Erfahrungen und fassen diese zusammen. Diese Ergebnisse werden dann in einer gemeinsamen Abschlussveranstaltung diskutiert.

**Arbeitsaufwand:** 180h = 56h Präsenszeit + 124h selbständige Arbeit am Projekt

<table border="1" id="bkmrk-studien-%2Fpr%C3%BCfungslei" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 32.6591%;"></col><col style="width: 35.9941%;"></col><col style="width: 31.3468%;"></col></colgroup><tbody><tr><td>**Prüfungsvorleistungen:**</td><td>**Studien-/Prüfungsleistungen:**</td><td>**Lehrform / SWS:**</td></tr><tr><td style="vertical-align: top;">Projekt + Ausarbeitung

</td><td class="align-left" style="vertical-align: top;">mündliche Prürfung

</td><td class="align-left" style="vertical-align: top;">Blockseminar / Projektarbeit

</td></tr></tbody></table>

<table border="1" id="bkmrk-voraussetzungen-nach" style="font-family: var(--font-body); font-size: 14px; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Voraussetzungen nach Prüfungsordnung:**</td><td>**Empfohlene Voraussetzungen:**</td></tr><tr><td class="align-left" style="vertical-align: top;">keine

</td><td class="align-left" style="vertical-align: top;">Software Engineering

</td></tr></tbody></table>

<table border="1" id="bkmrk-medienformen%3A-litera" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Medienformen:**</td><td>**Literatur:**</td></tr><tr><td class="align-left" style="vertical-align: top;"></td><td class="align-left" style="vertical-align: top;"></td></tr></tbody></table>

**Hinweise:** Zuangsbeschränkung: Limitierte Teilnehmerzahl. Auswahlverfahren wird in erster Vorlesung bekannt gegeben

# Selected Chapters of IT Security: Orchestration of Mechanisms and Tools

##### Winter 


##### (in German: Selected Chapters of IT Security: Orchestration of Mechanisms and Tools )

<table bgcolor="#7FB3D9" border="1" id="bkmrk-%5Btitle%5D" style="width: 100%; border-collapse: collapse; border-width: 1px; border-style: none;"><colgroup><col style="width: 100%;"></col></colgroup><tbody><tr style="background-color: rgb(235, 243, 249);"><td>##### <span style="color: rgb(0, 104, 180);">**Module-ID:** </span><span style="color: rgb(0, 104, 180);">**FIN-INF-120505** </span>

</td></tr></tbody></table>

<table bgcolor="#7FB3D9" border="1" id="bkmrk-" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 13.061%;"></col><col style="width: 15.442%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col></colgroup><tbody><tr><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Abbreviation**</span>

<span style="color: rgb(61, 61, 61);">ITSEC-Orch </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Credit Points**</span>

<span style="color: rgb(61, 61, 61);">6 </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Semester**</span>

<span style="color: rgb(61, 61, 61);">Winter </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Term**</span>

<span style="color: #3d3d3d;">ab 1. </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);">**<span style="color: rgb(61, 61, 61);">Duration</span>**

<span style="color: rgb(61, 61, 61);">1 Semester </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Language**</span>

<span style="color: rgb(61, 61, 61);">english</span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Level**</span>

<span style="color: rgb(61, 61, 61);">Master </span>

</td></tr></tbody></table>

<table border="1" id="bkmrk-verantwortung%3A-verwe" style="border-collapse: collapse; width: 100%; height: 124.8px; border-width: 1px; border-style: none;"><colgroup><col style="width: 24.7879%;"></col><col style="width: 75.2121%;"></col></colgroup><tbody><tr style="height: 35.4px;"><td style="height: 35.4px;">**Link:**</td><td style="height: 35.4px;">[ LSF](https://lsf.ovgu.de/qislsf/rds?state=wsearchv&search=1&subdir=veranstaltung&veranstaltung.semester=20262&veranstaltung.dtxt=Selected+Chapters+of+IT+Security:+Orchestration+of+Mechanisms+and+Tools&P_start=0&P_anzahl=30&P.sort=veranstaltung.dtxt&_form=display "Selected Chapters of IT Security: Orchestration of Mechanisms and Tools")</td></tr><tr><td>**Limited accessability:**</td><td>false </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Responsibility:**</td><td style="height: 29.8px;">Prof. Dr.-Ing. Jana Dittmann </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Lecturer:**</td><td style="height: 29.8px;">Prof. Dr.-Ing. Jana Dittmann </td></tr><tr><td>**Classes:**</td><td>Projekt *Selected Chapters of IT-Security* </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Applicability in curriculum:**</td><td style="height: 29.8px;">- M.Sc. INF: Informatik  
- M.Sc. INF: Schlüssel- und Methodenkompetenzen  
- M.Sc. INF: Informatik Wahlpflicht (SPO 2027)  
- M.Sc. INF: Schlüssel- und Methodenkompetenz (SPO 2027)  
- M.Sc. INGINF: Informatik  
- M.Sc. INGINF: Schlüssel- und Methodenkompetenzen  
- M.Sc. WIF: Informatik  
- M.Sc. WIF: Schlüssel- und Methodenkompetenzen  
- M.Sc. WIF: Informatik Wahlpflicht (SPO 2027)  
- M.Sc. WIF: Schlüssel- und Methodenkompetenz (SPO 2027)  
- M.Sc. DKE: Applied Data Science  
- M.Sc. DE: Methoden der Informatik  
- M.Sc. DE: Informatik Wahlpflicht (SPO 2027)  
- M.Sc. VC: Computer Science  
- M.Sc. VC: Schlüssel- und Methodenkompetenzen  
- M.Sc. VC: Computer Science (SPO 2027)  
- M.Sc. VC: Schlüssel- und Methodenkompetenz (SPO 2027)  
  
</td></tr></tbody></table>

**Intended learning outcomes:** Die Studierenden ...

- kennen und verstehen Aspekte der Orchestrierung
- können ausgewählte Forschungsfragen der Orchestrierung selbständig bewältigen
- können bestehende Ansätze bewerten und kreativ für eine Forschungsfrage erweitern
- können sich in den semesterspezifischen Anwendungsfall einarbeiten und im Team reflektieren
- können für die Fragestellung neue Ansätze zur Orchestrierung aufzeigen
- können für den Semester-spezifischen Anwendungsfall Sicherheitsbedarfe feststellen und Verbesserungsalternativen vorschlagen
- können eine ausgewählte Lösung umsetzen, evaluieren und bewerten sowie Restrisiken aufzeigen
- können selbständig wissenschaftliche Methoden der IT-Sicherheit anwenden
- können die Ergebnisse wissenschaftlich in einem Referat präsentieren und sich einer Diskussion stellen
- können Herausforderungen in der Teamarbeit erkennen und reflektieren sowie angehen

  
**Content:** Inhalte zu aktuellen Herausforderungen und Lösungen der IT Sicherheit mit ausgewählten Fragen der Orchestrierung als technisch-organisatorische Gestaltungsaufgabe wie zum Beispiel aus:

- Sicherheitsmanagement Standardisierung,
- Zertifizierung und Evaluation Technische Gestaltung vor Rechtlichen Erwartungshorizonten
- ethische und sozial Aspekte der IT-Sicherheit einschließlich Nachhaltigkeit, digitale Inklusion und Barrierefreiheit
- Sicherheit im E-Business
- Fallstudien zur IT-Sicherheit

**Workload:** 28 h Präsenzzeit 152 h selbstständige Arbeit

<table border="1" id="bkmrk-studien-%2Fpr%C3%BCfungslei" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 32.0641%;"></col><col style="width: 34.9204%;"></col><col style="width: 33.0155%;"></col></colgroup><tbody><tr><td>**Pre-examination requirements:**</td><td>**Type of examination:**</td><td>**Teaching method / lecture hours per week (SWS):**</td></tr><tr><td>keine

</td><td>Hausarbeit

</td><td>Forschungsprojekt (2 SWS)

</td></tr></tbody></table>

<table border="1" id="bkmrk-voraussetzungen-nach" style="font-family: var(--font-body); font-size: 14px; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Prerequisites according to examination regulations:**</td><td>**Recommended prerequisites:**</td></tr><tr><td>keine

</td><td></td></tr></tbody></table>

<table border="1" id="bkmrk-medienformen%3A-litera" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Media:**</td><td>**Literature:**</td></tr><tr><td></td><td></td></tr></tbody></table>

**Comments:** [https://omen.cs.uni-magdeburg.de/itiamsl/deutsch/lehre/index.html](https://omen.cs.uni-magdeburg.de/itiamsl/deutsch/lehre/index.html)

# Seminar 'Advanced Topics of KMD'

##### every 


##### (in German: Seminar 'Advanced Topics of KMD' )

<table bgcolor="#7FB3D9" border="1" id="bkmrk-%5Btitle%5D" style="width: 100%; border-collapse: collapse; border-width: 1px; border-style: none;"><colgroup><col style="width: 100%;"></col></colgroup><tbody><tr style="background-color: rgb(235, 243, 249);"><td>##### <span style="color: rgb(0, 104, 180);">**Module-ID:** </span><span style="color: rgb(0, 104, 180);">**FIN-INF-120330** </span>

</td></tr></tbody></table>

<table bgcolor="#7FB3D9" border="1" id="bkmrk-" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 13.061%;"></col><col style="width: 15.442%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col></colgroup><tbody><tr><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Abbreviation**</span>

<span style="color: rgb(61, 61, 61);">AdvKMD\_Seminar </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Credit Points**</span>

<span style="color: rgb(61, 61, 61);">6 </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Semester**</span>

<span style="color: rgb(61, 61, 61);">every </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Term**</span>

<span style="color: #3d3d3d;">starting at 1. </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);">**<span style="color: rgb(61, 61, 61);">Duration</span>**

<span style="color: rgb(61, 61, 61);">1 Semester </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Language**</span>

<span style="color: rgb(61, 61, 61);">english</span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Level**</span>

<span style="color: rgb(61, 61, 61);">Master </span>

</td></tr></tbody></table>

<table border="1" id="bkmrk-verantwortung%3A-verwe" style="border-collapse: collapse; width: 100%; height: 124.8px; border-width: 1px; border-style: none;"><colgroup><col style="width: 24.7879%;"></col><col style="width: 75.2121%;"></col></colgroup><tbody><tr style="height: 35.4px;"><td style="height: 35.4px;">**Link:**</td><td style="height: 35.4px;">[ LSF](https://lsf.ovgu.de/qislsf/rds?state=wsearchv&search=1&subdir=veranstaltung&veranstaltung.semester=20261&veranstaltung.dtxt=Seminar+'Advanced+Topics+of+KMD'&P_start=0&P_anzahl=30&P.sort=veranstaltung.dtxt&_form=display "Seminar 'Advanced Topics of KMD'")</td></tr><tr><td>**Limited accessability:**</td><td>false </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Responsibility:**</td><td style="height: 29.8px;">Myra Spiliopoulou </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Lecturer:**</td><td style="height: 29.8px;">Myra Spiliopoulou </td></tr><tr><td>**Classes:**</td><td>Seminar *AdvKMD\_Seminar* </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Applicability in curriculum:**</td><td style="height: 29.8px;">- M.Sc. INF: Informatik  
- M.Sc. INF: Schlüssel- und Methodenkompetenzen  
- M.Sc. INGINF: Informatik  
- M.Sc. INGINF: Schlüssel- und Methodenkompetenzen  
- M.Sc. WIF: Wirtschaftsinformatik  
- M.Sc. WIF: Informatik  
- M.Sc. WIF: Schlüssel- und Methodenkompetenzen  
- M.Sc. DKE: Learning Methods and Models for Data Science  
- M.Sc. DKE: Data Processing for Data Science  
- M.Sc. DKE: Applied Data Science  
- M.Sc. DE: Methoden der Informatik  
- M.Sc. VC: Computer Science  
  
</td></tr></tbody></table>

**Intended learning outcomes:** When successfully completing this seminar, the students:

- know how to collect literature on a specific topic, and can judge which literature is relevant and which is not
- can compare mining methods, workflows and frameworks that address a specific scientific topic, and can rank them on given criteria
- can formulate such criteria themselves
- can critically discuss the advantages and caveats of a published mining method
- can summarize the papers they collected, their comparisons and critical discussion in an essay
- can present the papers they collected, their comparisons and critical discussion in a pre-specified amount of time and in a way understandable to both an audience that has read the papers and to an audience that has not read, and they can answer questions

  
**Content: CONTENT:** Topics on 'Advanced Knowledge Management and Discovery' for business applications, engineering applications and applications in healthcare; all topics refer to mining algorithms for static or dynamic data **STRUCTURE:** Each student receives a topic as assignment. The assignment encompasses:

- one or more 'seed' papers in the topic's area
- a series of questions to be answered, and which concern state of the art (SOTA) methods in the topic area, challenges addressed by these methods, evaluation criteria on the performance of these methods, evaluation procedures and datasets

The student must: 1. collect additional literature from the topic area in a transparent manner
2. compare the scientific advances in the collected literature in order to answer the scientific questions
3. critically discuss and rank the methods compared in the previous step
4. present the collected literature, the comparisons and the results in class
5. write an essay on them

**Workload:**

- 28 hours Seminar+Consultations in class
- 124 hours self-study work on scientific papers

  
<table border="1" id="bkmrk-studien-%2Fpr%C3%BCfungslei" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 32.0641%;"></col><col style="width: 34.9204%;"></col><col style="width: 33.0155%;"></col></colgroup><tbody><tr><td>**Pre-examination requirements:**</td><td>**Type of examination:**</td><td>**Teaching method / lecture hours per week (SWS):**</td></tr><tr><td></td><td>Referat

</td><td>Seminar (2 SWS)

</td></tr></tbody></table>

<table border="1" id="bkmrk-voraussetzungen-nach" style="font-family: var(--font-body); font-size: 14px; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Prerequisites according to examination regulations:**</td><td>**Recommended prerequisites:**</td></tr><tr><td>none

</td><td>- Familiarity with advanced mining methods
- Familiarity with procedures for the evaluation of models and the comparison of models
- Underpinnings of scientific writing (e.g. through a bachelor seminar or a bachelor thesis)

</td></tr></tbody></table>

<table border="1" id="bkmrk-medienformen%3A-litera" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Media:**</td><td>**Literature:**</td></tr><tr><td></td><td>The literature of the seminar covers several topics. For each topic, it consists of the papers assigned to each student and the paper that the student collects on that topic. The topics change in each semester.

</td></tr></tbody></table>

**Comments:** The seminar contains several topics. The mapping of the module (see field 'Verwendbarkeit') depends on the topic assigned to a specific student.

# Seminar on Advanced Topics of Predictive Maintenance

##### every 


##### (in German: Seminar on Advanced Topics of Predictive Maintenance )

<table bgcolor="#7FB3D9" border="1" id="bkmrk-%5Btitle%5D" style="width: 100%; border-collapse: collapse; border-width: 1px; border-style: none;"><colgroup><col style="width: 100%;"></col></colgroup><tbody><tr style="background-color: rgb(235, 243, 249);"><td>##### <span style="color: rgb(0, 104, 180);">**Module-ID:** </span><span style="color: rgb(0, 104, 180);">**FIN-INF-120489** </span>

</td></tr></tbody></table>

<table bgcolor="#7FB3D9" border="1" id="bkmrk-" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 13.061%;"></col><col style="width: 15.442%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col></colgroup><tbody><tr><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Abbreviation**</span>

<span style="color: rgb(61, 61, 61);">PredMa\_Masterseminar </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Credit Points**</span>

<span style="color: rgb(61, 61, 61);">6 </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Semester**</span>

<span style="color: rgb(61, 61, 61);">every </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Term**</span>

<span style="color: #3d3d3d;">starting at 1. </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);">**<span style="color: rgb(61, 61, 61);">Duration</span>**

<span style="color: rgb(61, 61, 61);">1 Semester </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Language**</span>

<span style="color: rgb(61, 61, 61);">english</span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Level**</span>

<span style="color: rgb(61, 61, 61);">Master </span>

</td></tr></tbody></table>

<table border="1" id="bkmrk-verantwortung%3A-verwe" style="border-collapse: collapse; width: 100%; height: 124.8px; border-width: 1px; border-style: none;"><colgroup><col style="width: 24.7879%;"></col><col style="width: 75.2121%;"></col></colgroup><tbody><tr style="height: 35.4px;"><td style="height: 35.4px;">**Link:**</td><td style="height: 35.4px;">[ LSF](https://lsf.ovgu.de/qislsf/rds?state=wsearchv&search=1&subdir=veranstaltung&veranstaltung.semester=20261&veranstaltung.dtxt=Seminar+on+Advanced+Topics+of+Predictive+Maintenance&P_start=0&P_anzahl=30&P.sort=veranstaltung.dtxt&_form=display "Seminar on Advanced Topics of Predictive Maintenance")</td></tr><tr><td>**Limited accessability:**</td><td>true </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Responsibility:**</td><td style="height: 29.8px;">Prof. Dr.-Ing. Benjamin Noack, Prof. Dr. Myra Spiliopoulou </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Lecturer:**</td><td style="height: 29.8px;">Prof. Dr.-Ing. Benjamin Noack, Prof. Dr. Myra Spiliopoulou </td></tr><tr><td>**Classes:**</td><td>- Seminar *Advanced Topics of Predictive Maintenance*

 </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Applicability in curriculum:**</td><td style="height: 29.8px;">- M.Sc. INF: Informatik  
- M.Sc. INF: Schlüssel- und Methodenkompetenzen  
- M.Sc. INF: Informatik Wahlpflicht (SPO 2027)  
- M.Sc. INF: Schlüssel- und Methodenkompetenz (SPO 2027)  
- M.Sc. INGINF: Informatik  
- M.Sc. INGINF: Schlüssel- und Methodenkompetenzen  
- M.Sc. WIF: Wirtschaftsinformatik  
- M.Sc. WIF: Informatik  
- M.Sc. WIF: Schlüssel- und Methodenkompetenzen  
- M.Sc. WIF: Informatik Wahlpflicht (SPO 2027)  
- M.Sc. WIF: Wirtschaftsinformatik (SPO 2027)  
- M.Sc. WIF: Schlüssel- und Methodenkompetenz (SPO 2027)  
- M.Sc. DKE: Learning Methods and Models for Data Science  
- M.Sc. DKE: Applied Data Science  
- M.Sc. DE: Methoden des Digital Engineering  
- M.Sc. DE: Methoden der Informatik  
- M.Sc. DE: Digital Engineering (SPO 2027)  
- M.Sc. DE: Schlüssel- und Methodenkompetenz (SPO 2027)  
- M.Sc. VC: Computer Science  
- M.Sc. VC: Computer Science (SPO 2027)  
  
</td></tr></tbody></table>

**Intended learning outcomes:** Students who complete the course ...

- read scientific articles given to them on introductory topics of predictive maintenance
- discuss these articles and reflect on them
- compare the methods that appear in these articles and discuss the pros and contra of each method in comparison to other methods
- summarize article contents on predictive maintenance in a report and present them
- formulate questions on these articles and answer questions formulated by other seminar participants

  
**Content:** In this seminar, the participants will learn about

- challenges and methods for data acquisition in industrial processes
- data analysis tools in predictive maintenance
- process modeling, fault detection, and state prediction for industrial applications

**Workload:** 28h in presence (consultation meetings, presentations) + 156 h self study

<table border="1" id="bkmrk-studien-%2Fpr%C3%BCfungslei" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 32.0641%;"></col><col style="width: 34.9204%;"></col><col style="width: 33.0155%;"></col></colgroup><tbody><tr><td>**Pre-examination requirements:**</td><td>**Type of examination:**</td><td>**Teaching method / lecture hours per week (SWS):**</td></tr><tr><td></td><td>Referat

</td><td>Seminar (2 SWS)

</td></tr></tbody></table>

<table border="1" id="bkmrk-voraussetzungen-nach" style="font-family: var(--font-body); font-size: 14px; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Prerequisites according to examination regulations:**</td><td>**Recommended prerequisites:**</td></tr><tr><td>none

</td><td>- Signal and information processing
- Learning algorithms
- Underpinnings of engineering sciences and/or business informatics (some topics only)
- Principles of scientific writing

</td></tr></tbody></table>

<table border="1" id="bkmrk-medienformen%3A-litera" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Media:**</td><td>**Literature:**</td></tr><tr><td></td><td>Literature depends on topic assignment and is given to each student together with the assignment

</td></tr></tbody></table>

**Comments:**

# Sensor Networks Seminar

##### Winter 


##### (in German: Sensor Networks Seminar )

<table bgcolor="#7FB3D9" border="1" id="bkmrk-%5Btitle%5D" style="width: 100%; border-collapse: collapse; border-width: 1px; border-style: none;"><colgroup><col style="width: 100%;"></col></colgroup><tbody><tr style="background-color: rgb(235, 243, 249);"><td>##### <span style="color: rgb(0, 104, 180);">**Module-ID:** </span><span style="color: rgb(0, 104, 180);">**FIN-INF-120514** </span>

</td></tr></tbody></table>

<table bgcolor="#7FB3D9" border="1" id="bkmrk-" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 13.061%;"></col><col style="width: 15.442%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col></colgroup><tbody><tr><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Abbreviation**</span>

<span style="color: rgb(61, 61, 61);">SN </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Credit Points**</span>

<span style="color: rgb(61, 61, 61);">6 </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Semester**</span>

<span style="color: rgb(61, 61, 61);">Winter </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Term**</span>

<span style="color: #3d3d3d;">ab 1. </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);">**<span style="color: rgb(61, 61, 61);">Duration</span>**

<span style="color: rgb(61, 61, 61);">1 Semester </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Language**</span>

<span style="color: rgb(61, 61, 61);">english</span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Level**</span>

<span style="color: rgb(61, 61, 61);">Master </span>

</td></tr></tbody></table>

<table border="1" id="bkmrk-verantwortung%3A-verwe" style="border-collapse: collapse; width: 100%; height: 124.8px; border-width: 1px; border-style: none;"><colgroup><col style="width: 24.7879%;"></col><col style="width: 75.2121%;"></col></colgroup><tbody><tr style="height: 35.4px;"><td style="height: 35.4px;">**Link:**</td><td style="height: 35.4px;">[ LSF](https://lsf.ovgu.de/qislsf/rds?state=wsearchv&search=1&subdir=veranstaltung&veranstaltung.semester=20262&veranstaltung.dtxt=Sensor+Networks+Seminar&P_start=0&P_anzahl=30&P.sort=veranstaltung.dtxt&_form=display "Sensor Networks Seminar")</td></tr><tr><td>**Limited accessability:**</td><td>true </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Responsibility:**</td><td style="height: 29.8px;">Prof. Dr.-Ing. Benjamin Noack </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Lecturer:**</td><td style="height: 29.8px;">Prof. Dr.-Ing. Benjamin Noack </td></tr><tr><td>**Classes:**</td><td>Seminar *Sensor Networks* </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Applicability in curriculum:**</td><td style="height: 29.8px;">- M.Sc. INF: Informatik  
- M.Sc. INF: Schlüssel- und Methodenkompetenzen  
- M.Sc. INF: Informatik Wahlpflicht (SPO 2027)  
- M.Sc. INF: Schlüssel- und Methodenkompetenz (SPO 2027)  
- M.Sc. INGINF: Informatik  
- M.Sc. INGINF: Schlüssel- und Methodenkompetenzen  
- M.Sc. WIF: Informatik  
- M.Sc. WIF: Schlüssel- und Methodenkompetenzen  
- M.Sc. WIF: Informatik Wahlpflicht (SPO 2027)  
- M.Sc. WIF: Schlüssel- und Methodenkompetenz (SPO 2027)  
- M.Sc. DKE: Applied Data Science  
- M.Sc. DE: Methoden des Digital Engineering  
- M.Sc. DE: Methoden der Informatik  
- M.Sc. DE: Fachliche Spezialisierung  
- M.Sc. VC: Schlüssel- und Methodenkompetenzen  
- M.Sc. VC: Schlüssel- und Methodenkompetenz (SPO 2027)  
  
</td></tr></tbody></table>

**Intended learning outcomes:** Students who complete the course ...

- ​can independently research complex topics
- write clear scientific articles
- present informative and understandable scientific talks
- understand challenges and methods in sensor networks
- understand how to these challenges are addressed in practical applications of sensor networks

  
**Content:** In this seminar, the participants will learn about

- challenges and methods used in sensor networks
- the variety of applications and application-specific sensor network design

**Workload:** 28 h in presence (consultation meetings, presentations) + 156 h self study

<table border="1" id="bkmrk-studien-%2Fpr%C3%BCfungslei" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 32.0641%;"></col><col style="width: 34.9204%;"></col><col style="width: 33.0155%;"></col></colgroup><tbody><tr><td>**Pre-examination requirements:**</td><td>**Type of examination:**</td><td>**Teaching method / lecture hours per week (SWS):**</td></tr><tr><td></td><td>- Presentation
- Discussion
- Scientific Article

(Referat und Hausarbeit) </td><td>Seminar (2 SWS)

</td></tr></tbody></table>

<table border="1" id="bkmrk-voraussetzungen-nach" style="font-family: var(--font-body); font-size: 14px; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Prerequisites according to examination regulations:**</td><td>**Recommended prerequisites:**</td></tr><tr><td>keine

</td><td>- Lecture *Introduction to Distributed Sensor Data Fusion*
- Learning algorithms
- Underpinnings of engineering sciences and/or business informatics (some topics only)
- Principles of scientific writing

</td></tr></tbody></table>

<table border="1" id="bkmrk-medienformen%3A-litera" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Media:**</td><td>**Literature:**</td></tr><tr><td></td><td>Literature depends on topic assignment and is given to each student together with the assignment

</td></tr></tbody></table>

**Comments:**

# Service Engineering

**Sommer**


(engl. Service Engineering )

<table bgcolor="#7FB3D9" border="1" id="bkmrk-%5Btitle%5D" style="width: 100%; border-collapse: collapse; border-width: 1px; border-style: none;"><colgroup><col style="width: 100%;"></col></colgroup><tbody><tr style="background-color: rgb(235, 243, 249);"><td>##### <span style="color: rgb(0, 104, 180);">**Modulnummer: FIN-INF-120530** </span>

</td></tr></tbody></table>

<table bgcolor="#7FB3D9" border="1" id="bkmrk-" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 13.061%;"></col><col style="width: 15.442%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col></colgroup><tbody><tr><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Kürzel**</span>

<span style="color: rgb(61, 61, 61);"></span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**CP**</span>

<span style="color: rgb(61, 61, 61);">6 </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Semester**</span>

<span style="color: rgb(61, 61, 61);">Sommer </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Fachsem.**</span>

<span style="color: #3d3d3d;">ab 1. </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);">**<span style="color: rgb(61, 61, 61);">Dauer</span>**

<span style="color: rgb(61, 61, 61);">1 Semester </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Sprache**</span>

<span style="color: rgb(61, 61, 61);">deutsch</span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Niveau**</span>

<span style="color: rgb(61, 61, 61);">Master </span>

</td></tr></tbody></table>

<table border="1" id="bkmrk-verantwortung%3A-verwe" style="border-collapse: collapse; width: 100%; height: 89.3907px; border-width: 1px; border-style: none;"><colgroup><col style="width: 20.2601%;"></col><col style="width: 79.7399%;"></col></colgroup><tbody><tr><td>**Link zum LSF:**</td><td>[ LSF](https://lsf.ovgu.de/qislsf/rds?state=wsearchv&search=1&subdir=veranstaltung&veranstaltung.semester=20261&veranstaltung.dtxt=Service+Engineering&P_start=0&P_anzahl=30&P.sort=veranstaltung.dtxt&_form=display "Service Engineering")</td></tr><tr><td>**Zugang beschränkt:**</td><td></td></tr><tr style="height: 29.7969px;"><td style="height: 29.7969px;">**Verantwortung:**</td><td style="height: 29.7969px;">Prof. Dr. Frank Ortmeier </td></tr><tr style="height: 29.7969px;"><td style="height: 29.7969px;">**Dozent:in:**</td><td style="height: 29.7969px;">Prof. Dr. Andreas Schmietendorf (HWR Berlin) </td></tr><tr><td>**Lehrveranstaltungen:**</td><td>- Vorlesung *Service Engineering*
- Übung *Service Engineering*

</td></tr><tr style="height: 29.7969px;"><td style="height: 29.7969px;">**Verwendbarkeit:**</td><td style="height: 29.7969px;">- M.Sc. INF: Informatik  
- M.Sc. INGINF: Informatik  
- M.Sc. WIF: Wirtschaftsinformatik  
- M.Sc. WIF: Informatik  
- M.Sc. DKE: Applied Data Science  
  
</td></tr></tbody></table>

**Angestrebte Lernergebnisse:** Die Studierenden ...

- kennen die Auswirkungen serviceorientierter Architekturansätze auf den gesamten Lebenszyklus derart implementierter Lösungen,
- kennen Herausforderungen (Technologie, Prozesse, Organisation, …) serviceorientierter Integrationslösungen und einhergehende Lösungsalternativen,
- können benötigte Services modellgetrieben herleiten und erstellen bzw. Kriterien basiert bewerten (make or buy),
- kennen aktuelle Technologieansätze zur Implementierung benötigter Services und können ausgewählte Vertreter prototypisch anwenden,
- können Servicekompositionen aus Sicht der Modellierung und Implementierung (Low- und High –Code) erstellen bzw. das benötigte Management anwenden.

  
**Inhalt:** Überblick

- Die Vorlesung vermittelt zunächst die geschäfts-, organisations- und prozessbezogenen Ursachen API-basierter Integrationslösungen. In diesem Zusammenhang wird auf domänenspezifische (Referenz-) Modellansätze aus dem industriellen Umfeld (Telekommunikation, Banken, Versicherungen, …) eingegangen.
- Darauf aufbauend lernen die Studierenden die Funktionen von Integrationsplattformen (u.a. API-Management) kennen, welche API-Kompositionen über deren gesamten Lebenszyklus unterstützen bzw. verwalten.
- Mit Hilfe der ersten Komplexübung erfolgt dann eine quantitative Bewertung im Internet angebotenen Public- bzw. Open APIs.
- Eine weitere alternativ gestaltbare Komplexübung beschäftigt sich mit der Spezifikation, Modellierung, Entwicklung und Einbindung webbasierter APIs in (ggf. mobile) Applikationsszenarien.
- Im Mittelpunkt der abschließenden Komplexübung steht die Komposition von APIs, wobei abermals ein eigener Schwerpunkt (Modellsicht, Implementierung, Management) gewählt werden kann.

Themen: - Integrationslösungen als Treiber der Digitalisierung
- Integrieren statt Implementieren
- Basistechnologien für Web-APIs (Public- und Open APIs)
- Spezifikation, Entwicklung und Management von Web-APIs
- Prozess-Modellierung und -Implementierung (API-Komposition)

**Arbeitsaufwand:** 56 h Präsenz + 124 h selbstständige Arbeit

<table border="1" id="bkmrk-studien-%2Fpr%C3%BCfungslei" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 32.6591%;"></col><col style="width: 35.9941%;"></col><col style="width: 31.3468%;"></col></colgroup><tbody><tr><td>**Prüfungsvorleistungen:**</td><td>**Studien-/Prüfungsleistungen:**</td><td>**Lehrform / SWS:**</td></tr><tr><td style="vertical-align: top;"></td><td class="align-left" style="vertical-align: top;">Mündliche Prüfung

</td><td class="align-left" style="vertical-align: top;">- 2 SWS Vorlesung
- 2 SWS Übung

  
</td></tr></tbody></table>

<table border="1" id="bkmrk-voraussetzungen-nach" style="font-family: var(--font-body); font-size: 14px; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Voraussetzungen nach Prüfungsordnung:**</td><td>**Empfohlene Voraussetzungen:**</td></tr><tr><td class="align-left" style="vertical-align: top;">keine

</td><td class="align-left" style="vertical-align: top;">Software Engineering

</td></tr></tbody></table>

<table border="1" id="bkmrk-medienformen%3A-litera" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Medienformen:**</td><td>**Literatur:**</td></tr><tr><td class="align-left" style="vertical-align: top;"></td><td class="align-left" style="vertical-align: top;">- Hartenstein, S.; Nadobny, K.; Schmidt, S.; Schmietendorf, A.: Sicherheits- und Compliance-Management im Lebenszyklus von Web APIs, Logos-Verlag, Berlin, März 2020,
- Nitze, A.; Schmietendorf, A.: Bewertungsaspekte bei der agilen SW-Entwicklung …, Logos Verlag, Berlin 2014
- Schmietendorf, A.; Knuth, M.: Aspekte des Software Engineerings im Diskurs einer Low-Code orientierten Softwareentwicklung, Logos Verlag, Berlin 2024
- Sneed, H.; Sneed, S.: Web-basierte Systemintegration, Vieweg-Verlag, Braunschweig/Wiesbaden 2003
- Spichale, K.: API-Design, Praxishandbuch für Java-und Webservice-Entwickler, dpunkt.verlag, 2017
- Tilkov, S. et al.: REST und HTTP, dpunkt.verlag, Heidelberg 2015

  
</td></tr></tbody></table>

**Hinweise:**

# Software-Development for Industrial Robotics

**Winter**


(engl. Software-Development for Industrial Robotics )

<table bgcolor="#7FB3D9" border="1" id="bkmrk-%5Btitle%5D" style="width: 100%; border-collapse: collapse; border-width: 1px; border-style: none;"><colgroup><col style="width: 100%;"></col></colgroup><tbody><tr style="background-color: rgb(235, 243, 249);"><td>##### <span style="color: rgb(0, 104, 180);">**Modulnummer: FIN-INF-120432** </span>

</td></tr></tbody></table>

<table bgcolor="#7FB3D9" border="1" id="bkmrk-" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 13.061%;"></col><col style="width: 15.442%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col></colgroup><tbody><tr><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Kürzel**</span>

<span style="color: rgb(61, 61, 61);">SDIR </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**CP**</span>

<span style="color: rgb(61, 61, 61);">6 </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Semester**</span>

<span style="color: rgb(61, 61, 61);">Winter </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Fachsem.**</span>

<span style="color: #3d3d3d;">ab 1. </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);">**<span style="color: rgb(61, 61, 61);">Dauer</span>**

<span style="color: rgb(61, 61, 61);">1 Semester </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Sprache**</span>

<span style="color: rgb(61, 61, 61);">deutsch</span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Niveau**</span>

<span style="color: rgb(61, 61, 61);">Master </span>

</td></tr></tbody></table>

<table border="1" id="bkmrk-verantwortung%3A-verwe" style="border-collapse: collapse; width: 100%; height: 89.3907px; border-width: 1px; border-style: none;"><colgroup><col style="width: 20.2601%;"></col><col style="width: 79.7399%;"></col></colgroup><tbody><tr><td>**Link zum LSF:**</td><td>[ LSF](https://lsf.ovgu.de/qislsf/rds?state=wsearchv&search=1&subdir=veranstaltung&veranstaltung.semester=20262&veranstaltung.dtxt=Software-Development+for+Industrial+Robotics&P_start=0&P_anzahl=30&P.sort=veranstaltung.dtxt&_form=display "Software-Development for Industrial Robotics")</td></tr><tr><td>**Zugang beschränkt:**</td><td>true </td></tr><tr style="height: 29.7969px;"><td style="height: 29.7969px;">**Verantwortung:**</td><td style="height: 29.7969px;">Prof. Dr. Frank Ortmeier </td></tr><tr style="height: 29.7969px;"><td style="height: 29.7969px;">**Dozent:in:**</td><td style="height: 29.7969px;">Prof. Dr. Frank Ortmeier </td></tr><tr><td>**Lehrveranstaltungen:**</td><td>- Vorlesung *Software-Development for Industrial Robotics*
- Übung *Software-Development for Industrial Robotics*

</td></tr><tr style="height: 29.7969px;"><td style="height: 29.7969px;">**Verwendbarkeit:**</td><td style="height: 29.7969px;">- M.Sc. INF: Informatik  
- M.Sc. INGINF: Informatik  
- M.Sc. INGINF: Ingenieurinformatik  
- M.Sc. WIF: Informatik  
- M.Sc. DKE: Applied Data Science  
- M.Sc. DE: Methoden des Digital Engineering  
- M.Sc. DE: Methoden der Informatik  
- M.Sc. DE: Fachliche Spezialisierung  
- M.Sc. VC: Computer Science  
  
</td></tr></tbody></table>

**Angestrebte Lernergebnisse:** The students have ...

- Understanding of problems in the robotics domain
- Understanding and applicability of the mathematical background
- Practical experience in programming industrial robots on the basis of various tasks

  
**Inhalt:** The use of industrial robots is increasing rapidly these days. In 2014, the expected number of industrial robots increased by 27% compared to the previous year. The main reason is their flexibility, especially their ability to perform a wide range of tasks. In the lecture “Software Development for Industrial Robotics” an overview of this domain is given as well as the mathematical background. The latter deals in particular with the idea of forward and inverse kinematics, point-to-point movements, linear movements, trajectory planning, recognition of singularities, Denavit-Hartenberg convention, rotation and translation matrices. The final project deals with control using a collision-free path planner, KUKA youBot kinematics, numerical approaches to solving inverse kinematics, etc.

**Arbeitsaufwand:** 180h = 56h attendance time + 124h independent work

<table border="1" id="bkmrk-studien-%2Fpr%C3%BCfungslei" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 32.6591%;"></col><col style="width: 35.9941%;"></col><col style="width: 31.3468%;"></col></colgroup><tbody><tr><td>**Prüfungsvorleistungen:**</td><td>**Studien-/Prüfungsleistungen:**</td><td>**Lehrform / SWS:**</td></tr><tr><td style="vertical-align: top;">Projekt

</td><td class="align-left" style="vertical-align: top;">mündliche Prüfung

</td><td class="align-left" style="vertical-align: top;">- Lecture (2 SWS)
- Exercise (2 SWS)

  
</td></tr></tbody></table>

<table border="1" id="bkmrk-voraussetzungen-nach" style="font-family: var(--font-body); font-size: 14px; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Voraussetzungen nach Prüfungsordnung:**</td><td>**Empfohlene Voraussetzungen:**</td></tr><tr><td class="align-left" style="vertical-align: top;">none

</td><td class="align-left" style="vertical-align: top;"></td></tr></tbody></table>

<table border="1" id="bkmrk-medienformen%3A-litera" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Medienformen:**</td><td>**Literatur:**</td></tr><tr><td class="align-left" style="vertical-align: top;"></td><td class="align-left" style="vertical-align: top;"></td></tr></tbody></table>

**Hinweise:** Zuangsbeschränkung: Limitierte Teilnehmerzahl. Auswahlverfahren wird in erster Vorlesung bekannt gegeben

# Three-Dimensional & Advanced Interaction

##### Winter 


##### (in German: Three-Dimensional &amp; Advanced Interaction )

<table bgcolor="#7FB3D9" border="1" id="bkmrk-%5Btitle%5D" style="width: 100%; border-collapse: collapse; border-width: 1px; border-style: none;"><colgroup><col style="width: 100%;"></col></colgroup><tbody><tr style="background-color: rgb(235, 243, 249);"><td>##### <span style="color: rgb(0, 104, 180);">**Module-ID:** </span><span style="color: rgb(0, 104, 180);">**FIN-INF-120286** </span>

</td></tr></tbody></table>

<table bgcolor="#7FB3D9" border="1" id="bkmrk-" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 13.061%;"></col><col style="width: 15.442%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col></colgroup><tbody><tr><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Abbreviation**</span>

<span style="color: rgb(61, 61, 61);">TAI </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Credit Points**</span>

<span style="color: rgb(61, 61, 61);">6 </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Semester**</span>

<span style="color: rgb(61, 61, 61);">Winter </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Term**</span>

<span style="color: #3d3d3d;">starting at 1. </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);">**<span style="color: rgb(61, 61, 61);">Duration</span>**

<span style="color: rgb(61, 61, 61);">1 Semester </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Language**</span>

<span style="color: rgb(61, 61, 61);">english</span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Level**</span>

<span style="color: rgb(61, 61, 61);">Master </span>

</td></tr></tbody></table>

<table border="1" id="bkmrk-verantwortung%3A-verwe" style="border-collapse: collapse; width: 100%; height: 124.8px; border-width: 1px; border-style: none;"><colgroup><col style="width: 24.7879%;"></col><col style="width: 75.2121%;"></col></colgroup><tbody><tr style="height: 35.4px;"><td style="height: 35.4px;">**Link:**</td><td style="height: 35.4px;">[ LSF](https://lsf.ovgu.de/qislsf/rds?state=wsearchv&search=1&subdir=veranstaltung&veranstaltung.semester=20262&veranstaltung.dtxt=Three-Dimensional+&+Advanced+Interaction&P_start=0&P_anzahl=30&P.sort=veranstaltung.dtxt&_form=display "Three-Dimensional & Advanced Interaction")</td></tr><tr><td>**Limited accessability:**</td><td>true </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Responsibility:**</td><td style="height: 29.8px;">Christian Hansen </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Lecturer:**</td><td style="height: 29.8px;">Florian Heinrich </td></tr><tr><td>**Classes:**</td><td>- Lecture *Three-Dimensional &amp; Advanced Interaction*
- Seminar *Three-Dimensional &amp; Advanced Interaction*

 </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Applicability in curriculum:**</td><td style="height: 29.8px;">- M.Sc. INF: Informatik  
- M.Sc. INGINF: Informatik  
- M.Sc. WIF: Informatik  
- M.Sc. DKE: Applied Data Science  
- M.Sc. DE: Methoden der Informatik  
- M.Sc. VC: Visual Computing  
  
</td></tr></tbody></table>

**Intended learning outcomes:** Students ...

- understand the nature and importance of future user interfaces and the challenges and problems associated with them
- know, analyze and evaluate technologies, interaction techniques and methods for the development of advanced user interfaces
- are able to select suitable technologies and interaction techniques in the field of three-dimensional and modern Post-WIMP user interfaces
- have the ability to critically analyze scientific literature and knowledge of scientific publishing
- can conduct own research on a postgraduate level in the field of advanced user interfaces

  
**Content:**

- Introduction to Post-WIMP and Reality-based User Interfaces
- 3DInteraction: Tasks, Devices, 3D-Widgets,
- 3D UIs Augmented Reality Interaction
- Pen-based Interaction Techniques and Sketching
- Multitouch: Technologies, Gestures, Applications
- Gestural Interaction: Tracking, Freehand Gestures
- Tangible Interaction
- Advanced Topics: Gaze-based Interaction, Organic Interfaces, Everywhere Interfaces

**Workload:** 56h contact time + 124h self study

<table border="1" id="bkmrk-studien-%2Fpr%C3%BCfungslei" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 32.0641%;"></col><col style="width: 34.9204%;"></col><col style="width: 33.0155%;"></col></colgroup><tbody><tr><td>**Pre-examination requirements:**</td><td>**Type of examination:**</td><td>**Teaching method / lecture hours per week (SWS):**</td></tr><tr><td>Successful completion of the seminar (clarified in first lecture)

</td><td>Written exam

</td><td>- Lecture (2 SWS)
- Exercise class (2 SWS)

</td></tr></tbody></table>

<table border="1" id="bkmrk-voraussetzungen-nach" style="font-family: var(--font-body); font-size: 14px; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Prerequisites according to examination regulations:**</td><td>**Recommended prerequisites:**</td></tr><tr><td>keine

</td><td>Module *Interactive Systems*

</td></tr></tbody></table>

<table border="1" id="bkmrk-medienformen%3A-litera" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Media:**</td><td>**Literature:**</td></tr><tr><td></td><td>- Bowman, Kruijff, Laviola, Jr., Poupyrev: „3D User Interfaces: Theory and Practice“, Addison-Wesley, 2004
- Müller-Tomfelde (Ed.): „Tabletops – Horizontal Interactive Displays“, Springer, 2010
- Saffer: „Designing Gestural Interfaces“, O'Reilly Media, 2008
- Shaer, Hornecker: „Tangible User Interfaces: Past, Present and Future Directions“. In Foundations and Trends in Human-Computer Interaction, 3 (1), 2010

  
</td></tr></tbody></table>

**Comments:**

# VLBA - Systemarchitekturen

**Sommer**


(engl. VLBA: Systemarchitectures )

<table bgcolor="#7FB3D9" border="1" id="bkmrk-%5Btitle%5D" style="width: 100%; border-collapse: collapse; border-width: 1px; border-style: none;"><colgroup><col style="width: 100%;"></col></colgroup><tbody><tr style="background-color: rgb(235, 243, 249);"><td>##### <span style="color: rgb(0, 104, 180);">**Modulnummer: FIN-INF-120252** </span>

</td></tr></tbody></table>

<table bgcolor="#7FB3D9" border="1" id="bkmrk-" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 13.061%;"></col><col style="width: 15.442%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col></colgroup><tbody><tr><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Kürzel**</span>

<span style="color: rgb(61, 61, 61);">VLBA-SysA </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**CP**</span>

<span style="color: rgb(61, 61, 61);">9 </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Semester**</span>

<span style="color: rgb(61, 61, 61);">Sommer </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Fachsem.**</span>

<span style="color: #3d3d3d;">ab 1. </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);">**<span style="color: rgb(61, 61, 61);">Dauer</span>**

<span style="color: rgb(61, 61, 61);">1 Semester </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Sprache**</span>

<span style="color: rgb(61, 61, 61);">deutsch</span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Niveau**</span>

<span style="color: rgb(61, 61, 61);">Master </span>

</td></tr></tbody></table>

<table border="1" id="bkmrk-verantwortung%3A-verwe" style="border-collapse: collapse; width: 100%; height: 89.3907px; border-width: 1px; border-style: none;"><colgroup><col style="width: 20.2601%;"></col><col style="width: 79.7399%;"></col></colgroup><tbody><tr><td>**Link zum LSF:**</td><td>[ LSF](https://lsf.ovgu.de/qislsf/rds?state=wsearchv&search=1&subdir=veranstaltung&veranstaltung.semester=20261&veranstaltung.dtxt=VLBA+-+Systemarchitekturen&P_start=0&P_anzahl=30&P.sort=veranstaltung.dtxt&_form=display "VLBA - Systemarchitekturen")</td></tr><tr><td>**Zugang beschränkt:**</td><td>true </td></tr><tr style="height: 29.7969px;"><td style="height: 29.7969px;">**Verantwortung:**</td><td style="height: 29.7969px;">Prof. Dr. Klaus Turowski </td></tr><tr style="height: 29.7969px;"><td style="height: 29.7969px;">**Dozent:in:**</td><td style="height: 29.7969px;">Prof. Dr. Klaus Turowski </td></tr><tr><td>**Lehrveranstaltungen:**</td><td>- Vorlesung *VLBA: Systemarchitekturen*
- Übung *VLBA: Systemarchitekturen*

</td></tr><tr style="height: 29.7969px;"><td style="height: 29.7969px;">**Verwendbarkeit:**</td><td style="height: 29.7969px;">- M.Sc. INF: Informatik  
- M.Sc. INGINF: Informatik  
- M.Sc. WIF: Wirtschaftsinformatik  
- M.Sc. DKE: Applied Data Science  
- M.Sc. DE: Fachliche Spezialisierung  
- M.Sc. VC: Computer Science  
  
</td></tr></tbody></table>

**Angestrebte Lernergebnisse:** Die Studierenden ...

- sammeln Know-how über die Architektur von Systemlandschaften.
- wissen wie Geschäftsprozesse und IT-Ressourcen miteinander verbunden werden können (Wie spiegelt sich dies in der (System-)Architektur wider).
- kennen die Unterschiede zwischen monolithischen und serviceorientierten Architekturen bei der Entwicklung und Integration von Anwendungssystemen für Unternehmen.
- wissen, wie man Anwendungskomponenten zur Unterstützung verschiedener Geschäftsprozesse ableitet.
- wissen wie Komponenten und Dienste als Elemente einer Systemarchitektur systematisch identifiziert werden.
- wissen wie Cloud Computing-Technologien zur Unterstützung von Geschäftsprozessen genutzt werden können.
- kennen die Unterschiede zwischen den verschiedenen Cloud- Patterns und den Cloud-Service-Modellen.
- lernen die Cloud Application Architecture kennen und erfahren, wie die Microservice-Architektur die klassische serviceorientierte Architektur in Cloud-Umgebungen ergänzt.
- können sich selbstständig neues Wissen aneignen und für sich nutzbar machen.
- können bei ungewohnten Aufgabenstellungen eigene Ideen einbringen und Entscheidungen treffen.
- können für neue Aufgabenstellungen geeignete Lösungen auswählen, anwenden und anschließend bewerten.
- können die Ergebnisse wissenschaftlich in einem Referat präsentieren und sich einer Diskussion stellen.

  
**Inhalt:**

- Theorie der komponentenbasierten Systementwicklung
- Fachkomponenten,
- Frameworks,
- Komponenten-Lebenszyklen,
- CoBCoM-Architektur
- Architekturen von Systemlandschaften
- Pattern-Sprachen und Architektur-Pattern
- Service-orientierte Architektur (SoA)
- Web-Services
- Mediatoren
- Fallstudien
- Personal Information
- GuideShared ERP Architecture
- Inhaltsverzeichnis Teil A (Winter) Seite 250 – Teil A Inhaltsverzeichnis Teil B (Gesamt)
- S4/Hana und SAP Datasphere
- Prototypische Realisierung eines interorganisationalen Informationssystems auf Grundlage der CoBCoM-Architektur und SoA

**Arbeitsaufwand:** Präsenzzeiten:

```
28 h Vorlesung / 28 h Übung

```

Selbstständiges Arbeiten: ```
1. Vor- und Nachbereitung Vorlesung
2. Entwicklung einer auf maschinellem Lernen basierenden Lösung unter Anwendung von MLOps-Praktiken zur Lösung betriebswirtschaftlicher Probleme 

```

9 x30h (56 h Präsenzzeit + 214 h selbstständige Arbeit)   
<table border="1" id="bkmrk-studien-%2Fpr%C3%BCfungslei" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 32.6591%;"></col><col style="width: 35.9941%;"></col><col style="width: 31.3468%;"></col></colgroup><tbody><tr><td>**Prüfungsvorleistungen:**</td><td>**Studien-/Prüfungsleistungen:**</td><td>**Lehrform / SWS:**</td></tr><tr><td style="vertical-align: top;"></td><td class="align-left" style="vertical-align: top;">Referat

</td><td class="align-left" style="vertical-align: top;">- Vorlesung (2 SWS)
- Übung (2 SWS)

  
</td></tr></tbody></table>

<table border="1" id="bkmrk-voraussetzungen-nach" style="font-family: var(--font-body); font-size: 14px; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Voraussetzungen nach Prüfungsordnung:**</td><td>**Empfohlene Voraussetzungen:**</td></tr><tr><td class="align-left" style="vertical-align: top;">Version control systems, DevOps practicies (CI/CD), Containerization technologies, and python.

</td><td class="align-left" style="vertical-align: top;">Version control systems, DevOps practicies (CI/CD), Containerization technologies, and python.

</td></tr></tbody></table>

<table border="1" id="bkmrk-medienformen%3A-litera" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Medienformen:**</td><td>**Literatur:**</td></tr><tr><td class="align-left" style="vertical-align: top;"></td><td class="align-left" style="vertical-align: top;">- Turowski, K.: Fachkomponenten. Aachen 2002.
- Herden, S., Marx Gómez, J., Rautenstrauch, C., Zwanziger, A.: Softwarearchitekturen für E-Business-Systeme, Berlin, Heidelberg u. a., 2006.

  
</td></tr></tbody></table>

**Hinweise:**

# VLBA – Cloud DevOps Technologies

##### Winter 


##### (in German: VLBA – Cloud DevOps Technologies )

<table bgcolor="#7FB3D9" border="1" id="bkmrk-%5Btitle%5D" style="width: 100%; border-collapse: collapse; border-width: 1px; border-style: none;"><colgroup><col style="width: 100%;"></col></colgroup><tbody><tr style="background-color: rgb(235, 243, 249);"><td>##### <span style="color: rgb(0, 104, 180);">**Module-ID:** </span><span style="color: rgb(0, 104, 180);">**FIN-INF-120478** </span>

</td></tr></tbody></table>

<table bgcolor="#7FB3D9" border="1" id="bkmrk-" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 13.061%;"></col><col style="width: 15.442%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col></colgroup><tbody><tr><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Abbreviation**</span>

<span style="color: rgb(61, 61, 61);">VLBA-CDOT </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Credit Points**</span>

<span style="color: rgb(61, 61, 61);">9 </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Semester**</span>

<span style="color: rgb(61, 61, 61);">Winter </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Term**</span>

<span style="color: #3d3d3d;">starting at 1. </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);">**<span style="color: rgb(61, 61, 61);">Duration</span>**

<span style="color: rgb(61, 61, 61);">1 Semester </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Language**</span>

<span style="color: rgb(61, 61, 61);">english</span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Level**</span>

<span style="color: rgb(61, 61, 61);">Master </span>

</td></tr></tbody></table>

<table border="1" id="bkmrk-verantwortung%3A-verwe" style="border-collapse: collapse; width: 100%; height: 124.8px; border-width: 1px; border-style: none;"><colgroup><col style="width: 24.7879%;"></col><col style="width: 75.2121%;"></col></colgroup><tbody><tr style="height: 35.4px;"><td style="height: 35.4px;">**Link:**</td><td style="height: 35.4px;">[ LSF](https://lsf.ovgu.de/qislsf/rds?state=wsearchv&search=1&subdir=veranstaltung&veranstaltung.semester=20262&veranstaltung.dtxt=VLBA+%E2%80%93+Cloud+DevOps+Technologies&P_start=0&P_anzahl=30&P.sort=veranstaltung.dtxt&_form=display "VLBA – Cloud DevOps Technologies")</td></tr><tr><td>**Limited accessability:**</td><td>true </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Responsibility:**</td><td style="height: 29.8px;">Prof. Dr. Klaus Turowski </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Lecturer:**</td><td style="height: 29.8px;">Prof. Dr. Klaus Turowski </td></tr><tr><td>**Classes:**</td><td>- '- Lecture *VLBA Cloud DevOps Technologies*
    - Exercise *VLBA Cloud DevOps Technologies*
    - Consultation *VLBA - Cloud DevOps Technologien (Consultation)*
    - Tutorial *VLBA - Cloud DevOps Technologien (Tutorial)*

 </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Applicability in curriculum:**</td><td style="height: 29.8px;">- M.Sc. INF: Informatik  
- M.Sc. INGINF: Informatik  
- M.Sc. WIF: Wirtschaftsinformatik  
- M.Sc. WIF: Informatik  
- M.Sc. DKE: Data Processing for Data Science  
- M.Sc. DKE: Applied Data Science  
- M.Sc. DE: Methoden der Informatik  
- M.Sc. VC: Computer Science  
  
</td></tr></tbody></table>

**Intended learning outcomes:** Students ...

- know and understand specialized subject content that expands and deepens the Bachelor's degree.
- can independently analyze problems and identify alternative solutions. -know how to work with UNIX operating systems.
- are experienced in the theory and handling of container-based virtualization technologies such as Docker.
- know how to use higher programming languages (Python).
- know how to use various configuration and automation tools and languages such as Ansible, Salt and Terraform.
- have practical and theoretical knowledge of testing IT systems, particularly in relation to essential DevOps concepts such as Continuous Integration and Continuous Delivery.
- have the ability to design, create, test, commission and support IT systems.

  
**Content:** In view of highly networked applications, big data and cloud computing, the careful planning and construction of architectures and landscapes of the corresponding information systems is more important than ever. In many cases, the lifecycle of a system does not end with the delivery of the solution, but rather the subsequent operation, monitoring and maintenance have become an essential part of this process. At this point, sophisticated paradigms and methods are required to facilitate the continuous development and operation of these systems while preventing errors, failures and other disruptions. The course is designed to teach the fundamentals as well as initial practical experience in the development and Table of Contents Part A (Winter) Page 248 - Part A Table of Contents Part B (Full) operation (DevOps) of systems in conjunction with dedicated cloud technologies. In addition to the theoretical basics, essential concepts and technologies are discussed and applied that enable the continuous integration, delivery and testing of corresponding systems.

**Workload:** Attendance = 84 h: 21 h Lecture 21 h Exercise 21 h Consultation 21 h Tutorial Independend work = 186 h: 186 h working on several assignments that build on each other

<table border="1" id="bkmrk-studien-%2Fpr%C3%BCfungslei" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 32.0641%;"></col><col style="width: 34.9204%;"></col><col style="width: 33.0155%;"></col></colgroup><tbody><tr><td>**Pre-examination requirements:**</td><td>**Type of examination:**</td><td>**Teaching method / lecture hours per week (SWS):**</td></tr><tr><td>In order to qualify for the final project, certain requirements must be fulfilled. Details will be announced in the first lecture.

</td><td>Hausarbeit

</td><td>Vorlesung (2 SWS) Übung (2 SWS)

</td></tr></tbody></table>

<table border="1" id="bkmrk-voraussetzungen-nach" style="font-family: var(--font-body); font-size: 14px; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Prerequisites according to examination regulations:**</td><td>**Recommended prerequisites:**</td></tr><tr><td>keine

</td><td></td></tr></tbody></table>

<table border="1" id="bkmrk-medienformen%3A-litera" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Media:**</td><td>**Literature:**</td></tr><tr><td></td><td></td></tr></tbody></table>

**Comments:**

# Visual Analytics

##### Summer 


##### (in German: Visual Analytics )

<table bgcolor="#7FB3D9" border="1" id="bkmrk-%5Btitle%5D" style="width: 100%; border-collapse: collapse; border-width: 1px; border-style: none;"><colgroup><col style="width: 100%;"></col></colgroup><tbody><tr style="background-color: rgb(235, 243, 249);"><td>##### <span style="color: rgb(0, 104, 180);">**Module-ID:** </span><span style="color: rgb(0, 104, 180);">**FIN-INF-120524** </span>

</td></tr></tbody></table>

<table bgcolor="#7FB3D9" border="1" id="bkmrk-" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 13.061%;"></col><col style="width: 15.442%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col></colgroup><tbody><tr><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Abbreviation**</span>

<span style="color: rgb(61, 61, 61);"></span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Credit Points**</span>

<span style="color: rgb(61, 61, 61);">6 </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Semester**</span>

<span style="color: rgb(61, 61, 61);">Summer </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Term**</span>

<span style="color: #3d3d3d;">starting at 1. </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);">**<span style="color: rgb(61, 61, 61);">Duration</span>**

<span style="color: rgb(61, 61, 61);">1 Semester </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Language**</span>

<span style="color: rgb(61, 61, 61);">english</span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Level**</span>

<span style="color: rgb(61, 61, 61);">Master </span>

</td></tr></tbody></table>

<table border="1" id="bkmrk-verantwortung%3A-verwe" style="border-collapse: collapse; width: 100%; height: 124.8px; border-width: 1px; border-style: none;"><colgroup><col style="width: 24.7879%;"></col><col style="width: 75.2121%;"></col></colgroup><tbody><tr style="height: 35.4px;"><td style="height: 35.4px;">**Link:**</td><td style="height: 35.4px;">[ LSF](https://lsf.ovgu.de/qislsf/rds?state=wsearchv&search=1&subdir=veranstaltung&veranstaltung.semester=20261&veranstaltung.dtxt=Visual+Analytics&P_start=0&P_anzahl=30&P.sort=veranstaltung.dtxt&_form=display "Visual Analytics")</td></tr><tr><td>**Limited accessability:**</td><td>true </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Responsibility:**</td><td style="height: 29.8px;">Bernhard Preim </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Lecturer:**</td><td style="height: 29.8px;">Bernhard Preim </td></tr><tr><td>**Classes:**</td><td>- Lecture *Visual Analytics*
- Exercise class *Visual Analytics*

 </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Applicability in curriculum:**</td><td style="height: 29.8px;">- M.Sc. INF: Informatik  
- M.Sc. INGINF: Informatik  
- M.Sc. WIF: Informatik  
- M.Sc. DKE: Applied Data Science  
- M.Sc. DE: Methoden des Digital Engineering  
- M.Sc. DE: Methoden der Informatik  
- M.Sc. VC: Visual Computing  
  
</td></tr></tbody></table>

**Intended learning outcomes:** Students ...

- know machine learning methods and the visualization of their results
- apply this knowledge to analyse financial and business data
- use statistical methods to improve visual analytics solutions
- can assess and compare clustering methods

  
**Content:**

- Introduction: Potential and applications of Visual Analytics
- Visual Analytics based on clustering
- Visual Analytics based on subspace clustering and biclustering
- Visual Analytics with decision trees
- Visual Analytics with association rules
- Scatterplot-based visualizations
- Visual Analytics of events sequences
- Interaktive und Kooperative Methoden von Visual Analytics
- Visual Analytics im Gesundheitswesen

**Workload:** '- 56 contact hours + 124 h self study

<table border="1" id="bkmrk-studien-%2Fpr%C3%BCfungslei" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 32.0641%;"></col><col style="width: 34.9204%;"></col><col style="width: 33.0155%;"></col></colgroup><tbody><tr><td>**Pre-examination requirements:**</td><td>**Type of examination:**</td><td>**Teaching method / lecture hours per week (SWS):**</td></tr><tr><td></td><td>Written exam, 2 hours

</td><td>- 2 SWS Lecture
- 2 SWS Exercise class

</td></tr></tbody></table>

<table border="1" id="bkmrk-voraussetzungen-nach" style="font-family: var(--font-body); font-size: 14px; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Prerequisites according to examination regulations:**</td><td>**Recommended prerequisites:**</td></tr><tr><td>none

</td><td>- Lecture Visualization
- Knowledge of Data Analysis, for example Intelligent Data Analysis
- Data Mining
- Machine Learning
- Artificial Intelligence

</td></tr></tbody></table>

<table border="1" id="bkmrk-medienformen%3A-litera" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Media:**</td><td>**Literature:**</td></tr><tr><td>- Powerpoint presentation
- Whiteboard
- Videos

</td><td>- J. J. Thomas, K. A. Cook (Hrsg.): Illuminating the path: The research and development agenda for visual analytics. IEEE Computer Society 2005
- D. A. Keim, F. Mansmann, J. Schneidewind, J. Thomas, H. Ziegler: Visual analytics: Scope and challenges. Visual Data Mining, 2008
- Andrienko, N., Andrienko, G., Fuchs, G., Slingsby, A., Turkay, C., &amp; Wrobel, S. (2020). *Visual analytics for data scientists*. Springer Nature.
- Kohlhammer, J., Proff, D. U., &amp; Wiener, A. (2018). *Visual business analytics: effektiver Zugang zu Daten und Informationen*. dpunkt. verlag.

  
</td></tr></tbody></table>

**Comments:**

# Visual Analytics in Health Care

##### Winter 


##### (in German: Visual Analytics in Health Care )

<table bgcolor="#7FB3D9" border="1" id="bkmrk-%5Btitle%5D" style="width: 100%; border-collapse: collapse; border-width: 1px; border-style: none;"><colgroup><col style="width: 100%;"></col></colgroup><tbody><tr style="background-color: rgb(235, 243, 249);"><td>##### <span style="color: rgb(0, 104, 180);">**Module-ID:** </span><span style="color: rgb(0, 104, 180);">**FIN-INF-120476** </span>

</td></tr></tbody></table>

<table bgcolor="#7FB3D9" border="1" id="bkmrk-" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 13.061%;"></col><col style="width: 15.442%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col></colgroup><tbody><tr><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Abbreviation**</span>

<span style="color: rgb(61, 61, 61);">VAHC </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Credit Points**</span>

<span style="color: rgb(61, 61, 61);">3 </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Semester**</span>

<span style="color: rgb(61, 61, 61);">Winter </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Term**</span>

<span style="color: #3d3d3d;">starting at 1. </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);">**<span style="color: rgb(61, 61, 61);">Duration</span>**

<span style="color: rgb(61, 61, 61);">1 Semester </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Language**</span>

<span style="color: rgb(61, 61, 61);">english</span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Level**</span>

<span style="color: rgb(61, 61, 61);">Master </span>

</td></tr></tbody></table>

<table border="1" id="bkmrk-verantwortung%3A-verwe" style="border-collapse: collapse; width: 100%; height: 124.8px; border-width: 1px; border-style: none;"><colgroup><col style="width: 24.7879%;"></col><col style="width: 75.2121%;"></col></colgroup><tbody><tr style="height: 35.4px;"><td style="height: 35.4px;">**Link:**</td><td style="height: 35.4px;">[ LSF](https://lsf.ovgu.de/qislsf/rds?state=wsearchv&search=1&subdir=veranstaltung&veranstaltung.semester=20262&veranstaltung.dtxt=Visual+Analytics+in+Health+Care&P_start=0&P_anzahl=30&P.sort=veranstaltung.dtxt&_form=display "Visual Analytics in Health Care")</td></tr><tr><td>**Limited accessability:**</td><td>true </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Responsibility:**</td><td style="height: 29.8px;">Bernhard Preim </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Lecturer:**</td><td style="height: 29.8px;">Bernhard Preim </td></tr><tr><td>**Classes:**</td><td>'- Seminar *Visual Analytics in Health Care* </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Applicability in curriculum:**</td><td style="height: 29.8px;">- M.Sc. INGINF: Informatik  
- M.Sc. WIF: Informatik  
- M.Sc. DKE: Applied Data Science  
- M.Sc. DE: Methoden der Informatik  
- M.Sc. DE: Fachliche Spezialisierung  
- M.Sc. VC: Visual Computing  
  
</td></tr></tbody></table>

**Intended learning outcomes:** The students ...

- know specific visual analytics solutions that are used in public healthcare applications
- can interpret and evaluate public healthcare data
- present and explain visual analytics solutions in healthcare scenarios

  
**Content:**

- Overview: Potential and applications of Visual Analytics in Healthcare
- Visual Analytics in Public Health
- Visual Analytics in Clinical Medicine
- Visual Analytics for Detecting Adverse Drug Effects
- Visual Analytics in Epidemiology

**Workload:** 3 credit points = 90 h (28 h attendance time + 62 h independent work), grading scale according to examination regulations

<table border="1" id="bkmrk-studien-%2Fpr%C3%BCfungslei" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 32.0641%;"></col><col style="width: 34.9204%;"></col><col style="width: 33.0155%;"></col></colgroup><tbody><tr><td>**Pre-examination requirements:**</td><td>**Type of examination:**</td><td>**Teaching method / lecture hours per week (SWS):**</td></tr><tr><td></td><td>Examinations: student talk, seminar paper (10 pages)

</td><td>Seminar (3 SWS)

</td></tr></tbody></table>

<table border="1" id="bkmrk-voraussetzungen-nach" style="font-family: var(--font-body); font-size: 14px; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Prerequisites according to examination regulations:**</td><td>**Recommended prerequisites:**</td></tr><tr><td>none

</td><td>Visualization, Data Mining, Visual Analytics or Information Visualization

</td></tr></tbody></table>

<table border="1" id="bkmrk-medienformen%3A-litera" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Media:**</td><td>**Literature:**</td></tr><tr><td>PowerPoint presentation, use of whiteboard, videos

</td><td>Workshop volumes of the IEEE Workshop Visual Analytics in Healthcare (since 2010), selected publications of other conferences / magazines in the fields of data analysis and visualization

</td></tr></tbody></table>

**Comments:** Auch anrechenbar für Studierende des Masterstudiengangs "Medical Systems Engineering".

# Visualization

##### Winter 


##### (in German: Visualization )

<table bgcolor="#7FB3D9" border="1" id="bkmrk-%5Btitle%5D" style="width: 100%; border-collapse: collapse; border-width: 1px; border-style: none;"><colgroup><col style="width: 100%;"></col></colgroup><tbody><tr style="background-color: rgb(235, 243, 249);"><td>##### <span style="color: rgb(0, 104, 180);">**Module-ID:** </span><span style="color: rgb(0, 104, 180);">**FIN-INF-102812** </span>

</td></tr></tbody></table>

<table bgcolor="#7FB3D9" border="1" id="bkmrk-" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 13.061%;"></col><col style="width: 15.442%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col></colgroup><tbody><tr><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Abbreviation**</span>

<span style="color: rgb(61, 61, 61);">VIS </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Credit Points**</span>

<span style="color: rgb(61, 61, 61);">6 </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Semester**</span>

<span style="color: rgb(61, 61, 61);">Winter </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Term**</span>

<span style="color: #3d3d3d;">starting at 1. </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);">**<span style="color: rgb(61, 61, 61);">Duration</span>**

<span style="color: rgb(61, 61, 61);">1 Semester </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Language**</span>

<span style="color: rgb(61, 61, 61);">english</span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Level**</span>

<span style="color: rgb(61, 61, 61);">Master </span>

</td></tr></tbody></table>

<table border="1" id="bkmrk-verantwortung%3A-verwe" style="border-collapse: collapse; width: 100%; height: 124.8px; border-width: 1px; border-style: none;"><colgroup><col style="width: 24.7879%;"></col><col style="width: 75.2121%;"></col></colgroup><tbody><tr style="height: 35.4px;"><td style="height: 35.4px;">**Link:**</td><td style="height: 35.4px;">[ LSF](https://lsf.ovgu.de/qislsf/rds?state=wsearchv&search=1&subdir=veranstaltung&veranstaltung.semester=20262&veranstaltung.dtxt=Visualization&P_start=0&P_anzahl=30&P.sort=veranstaltung.dtxt&_form=display "Visualization")</td></tr><tr><td>**Limited accessability:**</td><td>true </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Responsibility:**</td><td style="height: 29.8px;">Bernhard Preim </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Lecturer:**</td><td style="height: 29.8px;">Bernhard Preim </td></tr><tr><td>**Classes:**</td><td>- Lecture *Visualization*
- Exercise class *Visualization*

 </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Applicability in curriculum:**</td><td style="height: 29.8px;">- M.Sc. DKE: Applied Data Science  
- M.Sc. DE: Methoden der Informatik  
- M.Sc. DE: Informatik Wahlpflicht (SPO 2027)  
- M.Sc. VC: Visual Computing  
- M.Sc. VC: Visual Computing (SPO 2027)  
  
</td></tr></tbody></table>

**Intended learning outcomes:** Students ...

- understand how physiological perception affects visualization effectiveness
- know basic visualization techniques
- can generate appropriate visualizations for business and statistical data
- obtain a dataset with at least 100 observations and 5 attributes, formulate two analytical questions, and create data visualizations to answer these questions.

  
**Content:**

- Visualization goals and quality criteria
- Understanding of fundamentals of visual perception
- Overview of data structures in visualization
- Basic algorithms (Isolines, color scales, diagram techniques),
- Direct and indirect visualization of volume data
- map-based visualization
- dashboard design
- Information visualization

**Workload:** 56h contact time + 124h self study, students have to solve a comprehensive additional task where they analyze and visualize a multi-dimensional dataset

<table border="1" id="bkmrk-studien-%2Fpr%C3%BCfungslei" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 32.0641%;"></col><col style="width: 34.9204%;"></col><col style="width: 33.0155%;"></col></colgroup><tbody><tr><td>**Pre-examination requirements:**</td><td>**Type of examination:**</td><td>**Teaching method / lecture hours per week (SWS):**</td></tr><tr><td></td><td>Written exam, 2 hours

</td><td>- 2 SWS Lectures
- 2 SWS Exercise classes

</td></tr></tbody></table>

<table border="1" id="bkmrk-voraussetzungen-nach" style="font-family: var(--font-body); font-size: 14px; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Prerequisites according to examination regulations:**</td><td>**Recommended prerequisites:**</td></tr><tr><td>none

</td><td>- Module Computer Graphics I
- Modules Mathematics I, II and III

</td></tr></tbody></table>

<table border="1" id="bkmrk-medienformen%3A-litera" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Media:**</td><td>**Literature:**</td></tr><tr><td>- Powerpoint presentation
- Sketches
- Videos

</td><td>- P. and M. Keller (1994): Visual Cues, IEEE Computer Society PressT. Munzner (2015).
- Visualization Analysis and Design: Principles, Techniques, and Practice, A K Peters
- W. Schroeder, K. Martin, B. Lorensen (2001): The Visualization Toolkit: An object-oriented approach to 3d graphics, 3. Aufl. Springer, Heidelberg
- A. Telea (2014): Data Visualization: Principles and Practice, Second Edition, AK Peters (2. Auflage)
- M. Ward, D. Keim, G. Grinstein (2015): Interactive Data Visualization: Foundations, Techniques, and Applications, Second Edition

  
</td></tr></tbody></table>

**Comments:**

# Wissenschaftliches Individualprojekt

**jedes**


(engl. Individual Scientific Project )

<table bgcolor="#7FB3D9" border="1" id="bkmrk-%5Btitle%5D" style="width: 100%; border-collapse: collapse; border-width: 1px; border-style: none;"><colgroup><col style="width: 100%;"></col></colgroup><tbody><tr style="background-color: rgb(235, 243, 249);"><td>##### <span style="color: rgb(0, 104, 180);">**Modulnummer: FIN-INF-120301** </span>

</td></tr></tbody></table>

<table bgcolor="#7FB3D9" border="1" id="bkmrk-" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 13.061%;"></col><col style="width: 15.442%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col></colgroup><tbody><tr><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Kürzel**</span>

<span style="color: rgb(61, 61, 61);">WIP </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**CP**</span>

<span style="color: rgb(61, 61, 61);">6 </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Semester**</span>

<span style="color: rgb(61, 61, 61);">jedes </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Fachsem.**</span>

<span style="color: #3d3d3d;">ab 1. </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);">**<span style="color: rgb(61, 61, 61);">Dauer</span>**

<span style="color: rgb(61, 61, 61);">1 Semester </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Sprache**</span>

<span style="color: rgb(61, 61, 61);">deutsch</span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Niveau**</span>

<span style="color: rgb(61, 61, 61);">Master </span>

</td></tr></tbody></table>

<table border="1" id="bkmrk-verantwortung%3A-verwe" style="border-collapse: collapse; width: 100%; height: 89.3907px; border-width: 1px; border-style: none;"><colgroup><col style="width: 20.2601%;"></col><col style="width: 79.7399%;"></col></colgroup><tbody><tr><td>**Link zum LSF:**</td><td>[ LSF](https://lsf.ovgu.de/qislsf/rds?state=wsearchv&search=1&subdir=veranstaltung&veranstaltung.semester=20261&veranstaltung.dtxt=Wissenschaftliches+Individualprojekt&P_start=0&P_anzahl=30&P.sort=veranstaltung.dtxt&_form=display "Wissenschaftliches Individualprojekt")</td></tr><tr><td>**Zugang beschränkt:**</td><td></td></tr><tr style="height: 29.7969px;"><td style="height: 29.7969px;">**Verantwortung:**</td><td style="height: 29.7969px;">Studiendekan:in der FIN </td></tr><tr style="height: 29.7969px;"><td style="height: 29.7969px;">**Dozent:in:**</td><td style="height: 29.7969px;">Alle Dozenten der FIN </td></tr><tr><td>**Lehrveranstaltungen:**</td><td>keine </td></tr><tr style="height: 29.7969px;"><td style="height: 29.7969px;">**Verwendbarkeit:**</td><td style="height: 29.7969px;">- M.Sc. INF: Informatik  
- M.Sc. INF: Schlüssel- und Methodenkompetenz (SPO 2027)  
- M.Sc. INF: Projekte (SPO 2027)  
- M.Sc. INGINF: Informatik  
- M.Sc. INGINF: Ingenieurinformatik  
- M.Sc. WIF: Wirtschaftsinformatik  
- M.Sc. WIF: Informatik  
- M.Sc. WIF: Schlüssel- und Methodenkompetenz (SPO 2027)  
- M.Sc. WIF: Projekte (SPO 2027)  
- M.Sc. DKE: Learning Methods and Models for Data Science  
- M.Sc. DKE: Data Processing for Data Science  
- M.Sc. DKE: Applied Data Science  
- M.Sc. DKE: Projects (SPO 2027)  
- M.Sc. DE: Human Factors  
- M.Sc. DE: Methoden des Digital Engineering  
- M.Sc. DE: Methoden der Informatik  
- M.Sc. DE: Fachliche Spezialisierung  
- M.Sc. DE: Schlüssel- und Methodenkompetenz (SPO 2027)  
- M.Sc. DE: Projekte (SPO 2027)  
- M.Sc. VC: Visual Computing  
- M.Sc. VC: Computer Science  
- M.Sc. VC: Schlüssel- und Methodenkompetenz (SPO 2027)  
- M.Sc. VC: Projekte (SPO 2027)  
  
</td></tr></tbody></table>

**Angestrebte Lernergebnisse:** Die Studierenden ...

- arbeiten selbstständig an einer wissenschaftlichen Fragestellung
- arbeiten sich selbstständig in ein wissenschaftliches Spezialgebiet ein
- erarbeiten vertiefte Kenntnisse auf einem wissenschaftlichen Spezialgebiet
- präsentieren und interpretieren ihre Ergebnisse in mündlicher und/oder schriftlicher Form
- können ihren Erfolg und die Bedeutung ihrer Ergebnisse einschätzen
- beschreiben die Auswirkungen ihrer Entscheidungen auf den Verlauf und die Ergebnisse des Projektes

  
**Inhalt:** Die Studierenden bearbeiten in selbstständiger Arbeit eine individuell vereinbarte, wissenschaftliche Fragestellung unter Anleitung eines Hochschullehrers. Im Projekt entwickeln die Studierenden eine eigenständige Informatik-Lösung. Dadurch erwerben sie ein detailliertes und kritisches Verständnis in einem Spezialbereich der Informatik. Dieses Modul wird von unterschiedlichen Hochschullehrern implementiert. Die fachlichen Inhalte sind daher angebotsspezifisch.

**Arbeitsaufwand:** 180h selbstständige Arbeit

<table border="1" id="bkmrk-studien-%2Fpr%C3%BCfungslei" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 32.6591%;"></col><col style="width: 35.9941%;"></col><col style="width: 31.3468%;"></col></colgroup><tbody><tr><td>**Prüfungsvorleistungen:**</td><td>**Studien-/Prüfungsleistungen:**</td><td>**Lehrform / SWS:**</td></tr><tr><td style="vertical-align: top;"></td><td class="align-left" style="vertical-align: top;">Wissenschaftliches Projekt

</td><td class="align-left" style="vertical-align: top;">Angeleitetes wissenschaftliches Individualprojekt

</td></tr></tbody></table>

<table border="1" id="bkmrk-voraussetzungen-nach" style="font-family: var(--font-body); font-size: 14px; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Voraussetzungen nach Prüfungsordnung:**</td><td>**Empfohlene Voraussetzungen:**</td></tr><tr><td class="align-left" style="vertical-align: top;">keine

</td><td class="align-left" style="vertical-align: top;"></td></tr></tbody></table>

<table border="1" id="bkmrk-medienformen%3A-litera" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Medienformen:**</td><td>**Literatur:**</td></tr><tr><td class="align-left" style="vertical-align: top;"></td><td class="align-left" style="vertical-align: top;"></td></tr></tbody></table>

**Hinweise:** Projekte außerhalb der FIN müssen von Studiengangsleiter abgesegnet werden.

# Wissenschaftliches Individualprojekt (10 CP)

**jedes**


(engl. Individual Scientific Project )

<table bgcolor="#7FB3D9" border="1" id="bkmrk-%5Btitle%5D" style="width: 100%; border-collapse: collapse; border-width: 1px; border-style: none;"><colgroup><col style="width: 100%;"></col></colgroup><tbody><tr style="background-color: rgb(235, 243, 249);"><td>##### <span style="color: rgb(0, 104, 180);">**Modulnummer: FIN-INF-999851** </span>

</td></tr></tbody></table>

<table bgcolor="#7FB3D9" border="1" id="bkmrk-" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 13.061%;"></col><col style="width: 15.442%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col></colgroup><tbody><tr><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Kürzel**</span>

<span style="color: rgb(61, 61, 61);">WIP </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**CP**</span>

<span style="color: rgb(61, 61, 61);">10 </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Semester**</span>

<span style="color: rgb(61, 61, 61);">jedes </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Fachsem.**</span>

<span style="color: #3d3d3d;">ab 1. </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);">**<span style="color: rgb(61, 61, 61);">Dauer</span>**

<span style="color: rgb(61, 61, 61);">1 Semester </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Sprache**</span>

<span style="color: rgb(61, 61, 61);">deutsch</span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Niveau**</span>

<span style="color: rgb(61, 61, 61);">Master </span>

</td></tr></tbody></table>

<table border="1" id="bkmrk-verantwortung%3A-verwe" style="border-collapse: collapse; width: 100%; height: 89.3907px; border-width: 1px; border-style: none;"><colgroup><col style="width: 20.2601%;"></col><col style="width: 79.7399%;"></col></colgroup><tbody><tr><td>**Link zum LSF:**</td><td>[ LSF](https://lsf.ovgu.de/qislsf/rds?state=wsearchv&search=1&subdir=veranstaltung&veranstaltung.semester=20261&veranstaltung.dtxt=Wissenschaftliches+Individualprojekt+(10+CP)&P_start=0&P_anzahl=30&P.sort=veranstaltung.dtxt&_form=display "Wissenschaftliches Individualprojekt (10 CP)")</td></tr><tr><td>**Zugang beschränkt:**</td><td>false </td></tr><tr style="height: 29.7969px;"><td style="height: 29.7969px;">**Verantwortung:**</td><td style="height: 29.7969px;">Studiendekan:in der FIN </td></tr><tr style="height: 29.7969px;"><td style="height: 29.7969px;">**Dozent:in:**</td><td style="height: 29.7969px;">Alle Dozenten der FIN </td></tr><tr><td>**Lehrveranstaltungen:**</td><td>keine </td></tr><tr style="height: 29.7969px;"><td style="height: 29.7969px;">**Verwendbarkeit:**</td><td style="height: 29.7969px;">- M.Sc. INF: Schlüssel- und Methodenkompetenz (SPO 2027)  
- M.Sc. INF: Projekte (SPO 2027)  
- M.Sc. WIF: Schlüssel- und Methodenkompetenz (SPO 2027)  
- M.Sc. WIF: Projekte (SPO 2027)  
- M.Sc. DKE: Applied Data Science  
- M.Sc. DKE: Projects (SPO 2027)  
- M.Sc. DE: Schlüssel- und Methodenkompetenz (SPO 2027)  
- M.Sc. DE: Projekte (SPO 2027)  
- M.Sc. VC: Schlüssel- und Methodenkompetenz (SPO 2027)  
- M.Sc. VC: Projekte (SPO 2027)  
  
</td></tr></tbody></table>

**Angestrebte Lernergebnisse:** Die Studierenden ...

- arbeiten selbstständig an einer wissenschaftlichen Fragestellung
- arbeiten sich selbstständig in ein wissenschaftliches Spezialgebiet ein
- erarbeiten vertiefte Kenntnisse auf einem wissenschaftlichen Spezialgebiet
- präsentieren und interpretieren ihre Ergebnisse in mündlicher und/oder schriftlicher Form
- können ihren Erfolg und die Bedeutung ihrer Ergebnisse einschätzen
- beschreiben die Auswirkungen ihrer Entscheidungen auf den Verlauf und die Ergebnisse des Projektes

  
**Inhalt:** Die Studierenden bearbeiten in selbstständiger Arbeit eine individuell vereinbarte, wissenschaftliche Fragestellung unter Anleitung eines Hochschullehrers. Im Projekt entwickeln die Studierenden eine eigenständige Informatik-Lösung. Dadurch erwerben sie ein detailliertes und kritisches Verständnis in einem Spezialbereich der Informatik. Dieses Modul wird von unterschiedlichen Hochschullehrern implementiert. Die fachlichen Inhalte sind daher angebotsspezifisch.

**Arbeitsaufwand:** 300 h selbständige Arbeit

<table border="1" id="bkmrk-studien-%2Fpr%C3%BCfungslei" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 32.6591%;"></col><col style="width: 35.9941%;"></col><col style="width: 31.3468%;"></col></colgroup><tbody><tr><td>**Prüfungsvorleistungen:**</td><td>**Studien-/Prüfungsleistungen:**</td><td>**Lehrform / SWS:**</td></tr><tr><td style="vertical-align: top;"></td><td class="align-left" style="vertical-align: top;">Wissenschaftliches Projekt

</td><td class="align-left" style="vertical-align: top;">Angeleitetes wissenschaftliches Individualprojekt

</td></tr></tbody></table>

<table border="1" id="bkmrk-voraussetzungen-nach" style="font-family: var(--font-body); font-size: 14px; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Voraussetzungen nach Prüfungsordnung:**</td><td>**Empfohlene Voraussetzungen:**</td></tr><tr><td class="align-left" style="vertical-align: top;">keine

</td><td class="align-left" style="vertical-align: top;"></td></tr></tbody></table>

<table border="1" id="bkmrk-medienformen%3A-litera" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Medienformen:**</td><td>**Literatur:**</td></tr><tr><td class="align-left" style="vertical-align: top;"></td><td class="align-left" style="vertical-align: top;"></td></tr></tbody></table>

**Hinweise:**

# Wissenschaftliches Teamprojekt

**jedes**


(engl. Scientific Team Project )

<table bgcolor="#7FB3D9" border="1" id="bkmrk-%5Btitle%5D" style="width: 100%; border-collapse: collapse; border-width: 1px; border-style: none;"><colgroup><col style="width: 100%;"></col></colgroup><tbody><tr style="background-color: rgb(235, 243, 249);"><td>##### <span style="color: rgb(0, 104, 180);">**Modulnummer: FIN-INF-120482** </span>

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<table bgcolor="#7FB3D9" border="1" id="bkmrk-" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 13.061%;"></col><col style="width: 15.442%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col></colgroup><tbody><tr><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Kürzel**</span>

<span style="color: rgb(61, 61, 61);">WTP </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**CP**</span>

<span style="color: rgb(61, 61, 61);">6 </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Semester**</span>

<span style="color: rgb(61, 61, 61);">jedes </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Fachsem.**</span>

<span style="color: #3d3d3d;">ab 1. </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);">**<span style="color: rgb(61, 61, 61);">Dauer</span>**

<span style="color: rgb(61, 61, 61);">1 Semester </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Sprache**</span>

<span style="color: rgb(61, 61, 61);">deutsch</span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Niveau**</span>

<span style="color: rgb(61, 61, 61);">Master </span>

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<table border="1" id="bkmrk-verantwortung%3A-verwe" style="border-collapse: collapse; width: 100%; height: 89.3907px; border-width: 1px; border-style: none;"><colgroup><col style="width: 20.2601%;"></col><col style="width: 79.7399%;"></col></colgroup><tbody><tr><td>**Link zum LSF:**</td><td>[ LSF](https://lsf.ovgu.de/qislsf/rds?state=wsearchv&search=1&subdir=veranstaltung&veranstaltung.semester=20261&veranstaltung.dtxt=Wissenschaftliches+Teamprojekt&P_start=0&P_anzahl=30&P.sort=veranstaltung.dtxt&_form=display "Wissenschaftliches Teamprojekt")</td></tr><tr><td>**Zugang beschränkt:**</td><td></td></tr><tr style="height: 29.7969px;"><td style="height: 29.7969px;">**Verantwortung:**</td><td style="height: 29.7969px;">Studiendekan:in der FIN </td></tr><tr style="height: 29.7969px;"><td style="height: 29.7969px;">**Dozent:in:**</td><td style="height: 29.7969px;">Dozenten der FIN </td></tr><tr><td>**Lehrveranstaltungen:**</td><td>keine </td></tr><tr style="height: 29.7969px;"><td style="height: 29.7969px;">**Verwendbarkeit:**</td><td style="height: 29.7969px;">- M.Sc. INF: Informatik  
- M.Sc. INF: Schlüssel- und Methodenkompetenzen  
- M.Sc. INF: Schlüssel- und Methodenkompetenz (SPO 2027)  
- M.Sc. INF: Projekte (SPO 2027)  
- M.Sc. INGINF: Informatik  
- M.Sc. INGINF: Ingenieurinformatik  
- M.Sc. INGINF: Schlüssel- und Methodenkompetenzen  
- M.Sc. WIF: Wirtschaftsinformatik  
- M.Sc. WIF: Informatik  
- M.Sc. WIF: Schlüssel- und Methodenkompetenzen  
- M.Sc. WIF: Schlüssel- und Methodenkompetenz (SPO 2027)  
- M.Sc. WIF: Projekte (SPO 2027)  
- M.Sc. DKE: Applied Data Science  
- M.Sc. DKE: Projects (SPO 2027)  
- M.Sc. DE: Interdisziplinäres Team-Projekt  
- M.Sc. DE: Digital Engineering-Projekt  
- M.Sc. DE: Schlüssel- und Methodenkompetenz (SPO 2027)  
- M.Sc. DE: Projekte (SPO 2027)  
- M.Sc. VC: Schlüssel- und Methodenkompetenzen  
- M.Sc. VC: Schlüssel- und Methodenkompetenz (SPO 2027)  
- M.Sc. VC: Projekte (SPO 2027)  
  
</td></tr></tbody></table>

**Angestrebte Lernergebnisse:** Nach Abschluss des Moduls können die Studierenden …

- im Team eine komplexe Aufgabe aus dem Fachgebiet mit wissenschaftlichen Methoden bearbeiten
- Lösungsmöglichkeiten diskutieren und sich auf einen gemeinsamen Lösungsweg einigen, zu dem jeder seine Ideen einbringt,
- das benötigte Wissen erarbeiten und für das Team verfügbar machen
- mit anderen zusammen ein Projekt planen und lenken und für ihre eigene Rolle im Team die Verantwortung übernehmen
- das Team-Ergebnis präsentieren und beurteilen und ihre Entscheidungen verteidigen
- sich rückblickend mit der Ausübung ihrer Rolle im Team und ihrem Beitrag zum gemeinsamen Ergebnis auseinandersetzen

  
**Inhalt:** Dieses Modul wird von unterschiedlichen Hochschullehrern implementiert. Die fachlichen Inhalte sind daher angebotsspezifisch.

**Arbeitsaufwand:** 180 h selbstständige Arbeit

<table border="1" id="bkmrk-studien-%2Fpr%C3%BCfungslei" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 32.6591%;"></col><col style="width: 35.9941%;"></col><col style="width: 31.3468%;"></col></colgroup><tbody><tr><td>**Prüfungsvorleistungen:**</td><td>**Studien-/Prüfungsleistungen:**</td><td>**Lehrform / SWS:**</td></tr><tr><td style="vertical-align: top;"></td><td class="align-left" style="vertical-align: top;">Referat

</td><td class="align-left" style="vertical-align: top;">Wissenschaftliches Projekt

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<table border="1" id="bkmrk-voraussetzungen-nach" style="font-family: var(--font-body); font-size: 14px; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Voraussetzungen nach Prüfungsordnung:**</td><td>**Empfohlene Voraussetzungen:**</td></tr><tr><td class="align-left" style="vertical-align: top;">keine

</td><td class="align-left" style="vertical-align: top;"></td></tr></tbody></table>

<table border="1" id="bkmrk-medienformen%3A-litera" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Medienformen:**</td><td>**Literatur:**</td></tr><tr><td class="align-left" style="vertical-align: top;"></td><td class="align-left" style="vertical-align: top;"></td></tr></tbody></table>

**Hinweise:**

# Scientific Teamproject KMD

##### every 


##### (in German: Wissenschaftliches Teamprojekt KMD )

<table bgcolor="#7FB3D9" border="1" id="bkmrk-%5Btitle%5D" style="width: 100%; border-collapse: collapse; border-width: 1px; border-style: none;"><colgroup><col style="width: 100%;"></col></colgroup><tbody><tr style="background-color: rgb(235, 243, 249);"><td>##### <span style="color: rgb(0, 104, 180);">**Module-ID:** </span><span style="color: rgb(0, 104, 180);">**FIN-INF-120528** </span>

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<table bgcolor="#7FB3D9" border="1" id="bkmrk-" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 13.061%;"></col><col style="width: 15.442%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col><col style="width: 14.2515%;"></col></colgroup><tbody><tr><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Abbreviation**</span>

<span style="color: rgb(61, 61, 61);">Teamproj\_KMD </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Credit Points**</span>

<span style="color: rgb(61, 61, 61);">6 </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Semester**</span>

<span style="color: rgb(61, 61, 61);">every </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Term**</span>

<span style="color: #3d3d3d;">starting at 1. </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);">**<span style="color: rgb(61, 61, 61);">Duration</span>**

<span style="color: rgb(61, 61, 61);">1 Semester </span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Language**</span>

<span style="color: rgb(61, 61, 61);">english</span>

</td><td class="align-center" style="border: 5px solid rgb(255, 255, 255);"><span style="color: rgb(61, 61, 61);">**Level**</span>

<span style="color: rgb(61, 61, 61);">Master </span>

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<table border="1" id="bkmrk-verantwortung%3A-verwe" style="border-collapse: collapse; width: 100%; height: 124.8px; border-width: 1px; border-style: none;"><colgroup><col style="width: 24.7879%;"></col><col style="width: 75.2121%;"></col></colgroup><tbody><tr style="height: 35.4px;"><td style="height: 35.4px;">**Link:**</td><td style="height: 35.4px;">[ LSF](https://lsf.ovgu.de/qislsf/rds?state=wsearchv&search=1&subdir=veranstaltung&veranstaltung.semester=20261&veranstaltung.dtxt=Wissenschaftliches+Teamprojekt+KMD&P_start=0&P_anzahl=30&P.sort=veranstaltung.dtxt&_form=display "Wissenschaftliches Teamprojekt KMD")</td></tr><tr><td>**Limited accessability:**</td><td>false </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Responsibility:**</td><td style="height: 29.8px;">Myra Spiliopoulou </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Lecturer:**</td><td style="height: 29.8px;">Myra Spiliopoulou </td></tr><tr><td>**Classes:**</td><td>Teamproj\_KMD </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Applicability in curriculum:**</td><td style="height: 29.8px;">- M.Sc. INF: Informatik  
- M.Sc. INF: Schlüssel- und Methodenkompetenzen  
- M.Sc. INGINF: Informatik  
- M.Sc. INGINF: Schlüssel- und Methodenkompetenzen  
- M.Sc. WIF: Wirtschaftsinformatik  
- M.Sc. WIF: Informatik  
- M.Sc. WIF: Schlüssel- und Methodenkompetenzen  
- M.Sc. DKE: Applied Data Science  
- M.Sc. DE: Interdisziplinäres Team-Projekt  
- M.Sc. DE: Fachliche Spezialisierung  
- M.Sc. DE: Digital Engineering-Projekt  
- M.Sc. VC: Computer Science  
- M.Sc. VC: Schlüssel- und Methodenkompetenzen  
  
</td></tr></tbody></table>

**Intended learning outcomes: When completing this module successfully, the students can:**\* solve a realistic data mining and data engineering task in teamwork \* assess the business implications (costs and benefits) of a solution they propose \* built-up a team and organize themselves in it, distributing subtasks among themselves according to their competences, setting milestones and pursuing a joint schedule \* search for scientific papers of relevance \* search appropriate libraries for data preparation, learning and visualization \* design a learning workflow, apply AI methods and evaluate the induced models \* develop a software solution jointly, using public domain tools \* justify their design decisions and software suite selections \* present their work as a team \* write a joint report where they summarize and justify their approachBitte nachtragen nach neuen Constructive Alignment Vorgaben.

**Content: CONTENT:** Assignment in the form of a realistic task that involves the analysis of static or dynamic, structured or unstructured data with mining methods, including supervised, unsupervised and semi-supervised methods, stream miners, forecasters and elaborate AI tools. The assignment involves design, development and evaluation of a software solution in teamwork. **STRUCTURE:** The assignment is for a team of students, typically three; for larger teams, the assignment is extended to ensure that the effort of each student is 6 ECTS. The students are called to solve the task as a team. The task involves understanding a realistic problem, designing, developing and evaluating a solution for it, presenting this solution to the class, defending it and documenting it on paper.

**Workload:** For each team member: 28 h in class (including meetings) + 124 h self-study The teamproject is typically for three students. For larger teams, the assignments is extended to ensure that the effort of each team member is as above.

<table border="1" id="bkmrk-studien-%2Fpr%C3%BCfungslei" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 32.0641%;"></col><col style="width: 34.9204%;"></col><col style="width: 33.0155%;"></col></colgroup><tbody><tr><td>**Pre-examination requirements:**</td><td>**Type of examination:**</td><td>**Teaching method / lecture hours per week (SWS):**</td></tr><tr><td></td><td>- Wissenschaftliches Projekt, implementiert als eine Hausarbeit, die ein Referat beinhaltet

**COURTESY TRANSLATION:**  
This module implements the exam form 'Wissenschaftliches Projekt' as a 'Hausarbeit' which incorporates a 'Referat'. </td><td>Wissenschaftliches Teamprojekt (2 SWS)

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<table border="1" id="bkmrk-voraussetzungen-nach" style="font-family: var(--font-body); font-size: 14px; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Prerequisites according to examination regulations:**</td><td>**Recommended prerequisites:**</td></tr><tr><td>keine

</td><td>- Familiarity with advanced mining methods for static data and (for some assignments) for streams
- Familiarity with software development and software libraries
- Underpinnings of project management

</td></tr></tbody></table>

<table border="1" id="bkmrk-medienformen%3A-litera" style="border-collapse: collapse; width: 100%;"><colgroup><col style="width: 50%;"></col><col style="width: 50%;"></col></colgroup><tbody><tr><td>**Media:**</td><td>**Literature:**</td></tr><tr><td></td><td>Literature depends on topic assignment and is given to each team together with the assignment

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**Comments:** Als Implementierung des generischen **PFLICHTMODULS** "Wissenschaftliches Teamprojekt" entsprechend anrechenbar. **COURTESY TRANSLATION:**This module implements the **COMPULSORY** generic module 'Wissenschaftliches Teamprojekt'.