Advanced Topics in Deep Learning (Bachelor)
every
(in German: Advanced Topics in Deep Learning (Bachelor) )
Module-ID: FIN-INF-110502 |
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Abbreviation ATDL |
Credit Points 5 |
Semester every |
Term starting at 1. |
Duration 1 Semester |
Language english |
Level Bachelor |
| Link: | LSF |
| Limited accessability: | |
| Responsibility: | Sebastian Stober |
| Lecturer: | Sebastian Stober |
| Classes: | Advanced Topics in Deep Learning |
| Applicability in curriculum: | - B.Sc. INF: Informatik - Wahlpflicht - B.Sc. INF: Studienprofil: Künstliche Intelligenz - B.Sc. CV: Informatik - Wahlpflicht - B.Sc. INGINF: Informatik - Wahlpflicht - B.Sc. WIF: Gestalten und Anwenden - Wahlpflicht - B.Sc. INF (bilingual): Informatik - Wahlpflicht |
Intended learning outcomes:
The students ...
- are able to read and analyze current research papers
- can apply deep learning to an application domain
- gain in-depth knowledge in an application domain
- learn to work efficiently in a team on scientific problems
- learn to work on a server infrastructure
- present scientific results in a written and oral form
Content:
- Current topics from deep learning research
- Creation of domain-specific deep learning pipelines
- The application domain will be announced
beforehand
Workload:
30 contact hours + 120h self-study
| Pre-examination requirements: | Type of examination: | Teaching method / lecture hours per week (SWS): |
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Lecture/Seminar (2 SWS) |
| Prerequisites according to examination regulations: | Recommended prerequisites: |
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none |
Introduction to Deep Learning or Deep Learning for Engineers |
| Media: | Literature: |
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