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This entry is from Winter semester 2022/23 and might be obsolete. No current equivalent could be found.
CS 687 — Specialization Module Databionics for Time Series
(dt. Datenbionik für Zeitreihen)
Level, degree of commitment | Specialization module, compulsory elective module |
Forms of teaching and learning, workload |
Lecture (2 SWS), recitation class (2 SWS), 180 hours (60 h attendance, 120 h private study) |
Credit points, formal requirements |
6 CP Course requirement(s): Successful completion of at least 50 percent of the points from the weekly exercises. Examination type: Written or oral examination |
Language, Grading |
German,The grading is done with 0 to 15 points according to the examination regulations for the degree program M.Sc. Computer Science. |
Duration, frequency |
One semester, irregular |
Person in charge of the module's outline | Prof. Dr. Alfred Ultsch |
Contents
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.
Qualification Goals
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.
Prerequisites
None.
Applicability
The module can be attended at FB12 in study program(s)
- B.Sc. Data Science
- B.Sc. Computer Science
- B.Sc. Business Informatics
- M.Sc. Data Science
- M.Sc. Computer Science
- M.Sc. Mathematics
- M.Sc. Business Informatics
- M.Sc. Business Mathematics
When studying M.Sc. Computer Science, this module can be attended in the study area Specialization Modules in Computer Science.
The module can also be used in other study programs (export module).
The module is assigned to Practical Computer Science. Further information on eligibility can be found in the description of the study area.
Recommended Reading
- Depending on topic
Please note:
This page describes a module according to the latest valid module guide in Winter semester 2022/23. 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:
- Winter 2016/17 (no corresponding element)
- Summer 2018
- Winter 2018/19
- Winter 2019/20
- Winter 2020/21
- Summer 2021
- Winter 2021/22
- Winter 2022/23
- Winter 2023/24 (no corresponding element)
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.