Small Specialization Module Unsupervised Learning
(dt. Kleines Vertiefungsmodul Unsupervised Learning)
|Level, degree of commitment in original study programme||Advanced module, compulsory elective module|
|Forms of teaching and learning,
|Lecture (2 SWS), recitation class (2 SWS), |
180 hours (60 h attendance, 120 h private study)
Course requirement: Successful completion of at least 50 percent of the points from the weekly exercises.
Examination type: Written or oral examination
|German,The grading is done with 0 to 15 points according to the examination regulations for study course M.Sc. Computer Sciences.|
|Original study programme||M.Sc. Informatik / Vertiefungsbereich Informatik|
|One semester, |
|Person in charge of the module's outline||N.N.|
n.a. (see Qualification Goals and Business Event Announcements)
The students will
- acquire further knowledge and skills in Unsupervised Learning,
- become familiar with the theory of the respective area and get to know selected applications,
- practice fundamental methods of computer science,
- improve their oral communication skills in the exercises by practicing free speech in front of an audience and during discussion.
This page describes a module according to the latest valid module guide in Wintersemester 2019/20. Most rules valid for a module are not covered by the examination regulations and can therefore be updated on a semesterly basis. The following versions are available in the online module guide:
- WiSe 2016/17 (no corresponding element)
- SoSe 2018 (no corresponding element)
- WiSe 2018/19
- WiSe 2019/20
- WiSe 2020/21
- SoSe 2021
- WiSe 2021/22
The module guide contains all modules, independent of the current event offer. Please compare the current course catalogue in Marvin.
The information in this online module guide was created automatically. Legally binding is only the information in the examination regulations (Prüfungsordnung). If you notice any discrepancies or errors, we would be grateful for any advice.