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This entry is from Winter semester 2022/23 and might be obsolete. No current equivalent could be found.
Selected Topics in Mathematics / Data Science (Seminar)
(dt. Ausgewählte Themen der Mathematik / Data Science („Seminar“))
Level, degree of commitment | Advanced module, depends on importing study program |
Forms of teaching and learning, workload |
Seminar (2 SWS), 90 hours (30 h attendance, 60 h private study) |
Credit points, formal requirements |
3 CP Course requirement(s): Examination type: Presentation with written assignment |
Language, Grading |
German,The module is ungraded in accordance with the examination regulations for the degree program B.Sc. Data Science. |
Origin | B.Sc. Data Science |
Duration, frequency |
One semester, each semester |
Person in charge of the module's outline | All lecturers of Mathematics |
Contents
- Advanced mathematics topics, which approach the state of the art in research
- Topics are distributed to individual students or subject areas are distributed to small groups of students
- Familiarisation with the topic on the basis of scientific literature in self-study, supported by feedback from the lecturer
- One lecture per participant on the respective topic, largely free and comprehensible for the seminar participants
- Discussion about the lectures
Qualification Goals
The students shall
- work independently on a special mathematical topic,
- develop their ability to carry out scientific work independently,
- practice preparing and subdividing mathematical connections and supplementing them with explanatory content,
- acquire a safe handling of scientific literature and literature search,
- practice giving a structured presentation tailored to the audience's competences,
- deepen the handling of presentation media,
- deepen the ability for structured discussion of mathematical content in groups,
- further qualify themselves in the use of mathematical text typesetting programs during the writing of the seminar report.
Prerequisites
None. The competences taught in the following modules are recommended: either Foundations of Mathematics and Linear Algebra I and Linear Algebra II or Basic Linear Algebra, either Analysis I and Analysis II or Basic Real Analysis. In addition, the competences that are taught in the mathematical intermediate modules (depending on the topic) are recommended.
Applicability
The module can be attended at FB12 in study program(s)
- B.Sc. Data Science
When studying B.Sc. Data Science, this module can be attended in the study area Compulsory Elective Modules in Mathematics.
Recommended Reading
- According to the topic of the respective seminar
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.