# Applied Discrete Modelling

##### Winter 


##### (in German: Applied Discrete Modelling )

<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-120279** </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);">ADM </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>

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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=20262&veranstaltung.dtxt=Applied+Discrete+Modelling&P_start=0&P_anzahl=30&P.sort=veranstaltung.dtxt&_form=display "Applied Discrete Modelling")</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;">PD Dr. Claudia Krull </td></tr><tr style="height: 29.8px;"><td style="height: 29.8px;">**Lecturer:**</td><td style="height: 29.8px;">PD Dr. Claudia Krull </td></tr><tr><td>**Classes:**</td><td>- Lecture *Applied Discrete Modelling*
- Exercise class *Applied Discrete Modelling*

 </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. WIF: Informatik  
- M.Sc. WIF: Informatik Wahlpflicht (SPO 2027)  
- M.Sc. DKE: Learning Methods and Models for Data Science  
- M.Sc. DE: Fachliche Spezialisierung  
- M.Sc. DE: Informatik Wahlpflicht (SPO 2027)  
- M.Sc. VC: Computer Science  
- M.Sc. VC: Computer Science (SPO 2027)  
  
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**Intended learning outcomes:**

- Students understand the basics of Markov chains and know selected applications and solution methods
- Students understand non-Markovian stochastic processes and can model and simulate them in different ways
- Students understand hidden Markovian and non-Markovian processes
- Students know selected research topics of the research group
- Students can implement the models and methods they have learned and apply them to problems from the university's main research areas, in particular medicine and engineering

  
**Content:**

- Discrete-time and continuous-time Markov chains
- Applications and implementation of solution methods for Markov chains
- Method of supplementary variables
- Proxel simulation and phase distributions
- Modeling with hidden models
- Programming solution methods for different model classes
- Modeling and solving problems from medicine and engineering

**Workload:** 56 h lectures and exercise classes  
124 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>Solutions to Assignments 1-6 need to be handed in before the exam registration.

</td><td>Oral Exam 30 Minutes

</td><td>- Lecture 2 SWS
- Exercise class 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>none

</td><td>- Engineering mathematics
- Computer programming

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<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>recorded lectures and exercises are available

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**Comments:**