Specialization Module Databionics for Time Series
(dt. Datenbionik für Zeitreihen)
|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||Prof. Dr. Alfred Ultsch|
Based on basic knowledge of the analysis of time series, the knowledge discovery, knowledge representation and knowledge processing for multivariate time series will be dealt with in depth.
The students shall
- acquire in-depth knowledge and skills in the field of transmission of algorithms observed in nature for the treatment of time series,
- learn to apply the acquired knowledge and skills by means of selected applications,
- 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 2021/22. 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.