[ 921CGELPRMU13 ] UE Probabilistic Models

Workload Education level Study areas Responsible person Hours per week Coordinating university
1,5 ECTS M1 - Master's programme 1. year Computer Science Gerhard Widmer 1 hpw Johannes Kepler University Linz
Detailed information
Original study plan Master's programme Computer Science 2022W
Objectives To provide an opportunity for students to experiment with probabilistic models and reasoning methods, in order to better understand the workings and limitations of these methods. This class is highly recommended as a supplementary course to the VO "Probabilistic Models", where the theoretical foundations are explained.
Subject Practical experiments with probabilistic models. Development of simple systems that model and reason about some given problem. Specific focus: (discrete) Bayes Nets and temporal models (Hidden Markov Models, Kalman Filter).
Criteria for evaluation Independent experimenting based on given problem specifications. Written and/or oral report on the results.
Language English
Changing subject? No
On-site course
Maximum number of participants 35
Assignment procedure Direct assignment