inf534 - Probabilistic Modelling II (Complete module description)

inf534 - Probabilistic Modelling II (Complete module description)

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Module label Probabilistic Modelling II
Modulkürzel inf534
Credit points 3.0 KP
Workload 90 h
Institute directory Department of Computing Science
Verwendbarkeit des Moduls
  • Master's Programme Business Informatics (Master) > Akzentsetzungsmodule der Informatik
  • Master's Programme Computing Science (Master) > Angewandte Informatik
  • Master's Programme Engineering of Socio-Technical Systems (Master) > Embedded Brain Computer Interaction
Zuständige Personen
  • Fatikow, Sergej (module responsibility)
  • Marx Gómez, Jorge (module responsibility)
  • Lehrenden, Die im Modul (Prüfungsberechtigt)
Skills to be acquired in this module
Probabilistic models are generated with special tools (e.g. BUGS, JAGS, STAN) or domain specific programming languages (WebPPL, PyMC3, … , etc.). If they mimic cognitive processes of humans (e.g. pilots, drivers) or animals they could be used as cooperative assistance systems in technical or financial systems like cars, robots, or recommenders. In this part of the seminar we read, present, and discuss recent research papers.

Professional competence:
The students:
  • learn to connect problem- with model classes to come up with practical solutions

Methodological competence
The students:
  • acquire advanced skills in the design, implementation, and identification of probabilistic models with Bayesian methods
  • acquire knowledge about alternative machine learning methods

Social competence
The students:
  • learn to present and discuss probabilistic theories, methods, and models

The students:
  • reflect and evaluate chances and limitations of probabilistic approaches
  • learn to deliberate on machine-learning alternatives
Module contents
Theories, methods, and examples of Bayesian models with practical applications
Recent publications
Language of instruction German
Duration (semesters) 1 Semester
Module frequency halbjährlich
Module capacity unlimited
Reference text
Associated wiht the module:
  • inf533 Probabilistische Modellierung I
Examination Prüfungszeiten Type of examination
Final exam of module
individuell in Absprache mit dem Lehrenden
seminar talk, reflective written summary
Form of instruction Seminar
Frequency --
Workload Präsenzzeit 28 h