Stud.IP Uni Oldenburg
University of Oldenburg
20.10.2021 18:22:34
inf534 - Probabilistic Modelling II (Complete module description)
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Module label Probabilistic Modelling II
Module code inf534
Credit points 3.0 KP
Workload 90 h
Institute directory Department of Computing Science
Applicability of the module
  • Master's Programme Business Informatics (Master) > Akzentsetzungsmodule der Informatik
  • Master's Programme Computing Science (Master) > Angewandte Informatik
  • Master's Programme Embedded Systems and Microrobotics (Master) > Akzentsetzungsmodule
  • Master's Programme Engineering of Socio-Technical Systems (Master) > Embedded Brain Computer Interaction
Responsible persons
Möbus, Claus (Authorized examiners)
Lehrenden, Die im Modul (Authorized examiners)
Prerequisites
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


Self-competence
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
Reader's advisory
Recent publications
Links
Language of instruction German
Duration (semesters) 1 Semester
Module frequency halbjährlich
Module capacity unlimited
Reference text
Associated wiht the module:
  • inf533 Probabilistische Modellierung I
Modullevel / module level AS (Akzentsetzung / Accentuation)
Modulart / typ of module je nach Studiengang Pflicht oder Wahlpflicht
Lehr-/Lernform / Teaching/Learning method
Vorkenntnisse / Previous knowledge - Grundkenntnisse Progeammierung
Examination Time of examination Type of examination
Final exam of module
individuell in Absprache mit dem Lehrenden
seminar talk, reflective written summary
Course type Seminar
SWS 2
Frequency SuSe
Workload attendance 28 h