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Scientific Teamproject KMD

(in German: Wissenschaftliches Teamprojekt KMD - )

Module-ID: FIN-INF-999997
Link: LSF
Responsibility: Myra Spiliopoulou
Lecturer: Myra Spiliopoulou
Classes: Teamproj_KMD 
Applicability in curriculum: - 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: Methoden der Informatik
- M.Sc. DE: Fachliche Spezialisierung
- M.Sc. VC: Computer Science
- M.Sc. VC: Schlüssel- und Methodenkompetenzen

Abbreviation

Teamproj_KMD

Credit Points

6

Semester

every

Term

2.

Duration

1 Semester

Language

english

Level

Master

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.

Type of examination: Teaching method / lecture hours per week (SWS):

Referat

Wissenschaftliches Teamprojekt (2 SWS)

Prerequisites according to examination regulations: Recommended prerequisites:

keine

  • 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
Media: Literature:

Literature depends on topic assignment and is given to each team together with the assignment

Comments:
Als Implementierung des generischen PFLICHTMODULS "Wissenschaftliches Teamprojekt" entsprechend anrechenbar. COURTESY TRANSLATION: This module implements the COMPULSORY generic module 'Wissenschaftliches Teamprojekt'.