| Detailed information |
| Original study plan |
Master's programme Computer Science 2025W |
| Learning Outcomes |
Competences |
| See lecture series (Vorlesung) by the same name.
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| Skills |
Knowledge |
| See lecture series (Vorlesung) by the same name.
|
See lecture series (Vorlesung) by the same name.
|
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| Criteria for evaluation |
Implementation of, and experimentation with, simple algorithms, based on given problem specifications; written and/or oral report on the results.
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| Methods |
Students implement simple inference and learning algorithms related to probabilistic graphical models; they perform systematic experiments with toy problems and datasets, in order to deepen their understanding of probabilistic modeling and reasoning. Selected students report on their results and experiences in class.
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| Language |
English |
| Study material |
The lecture slides of the corresponding lecture series course (VO).
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| Changing subject? |
No |
| Further information |
This exercise course (UE) and the corresponding lecture series course (VO) form a didactic unit. The study results described here are achieved through the combination of these two courses.
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