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Advanced Topics in Deep Learning (Bachelor)

(in German: Advanced Topics in Deep Learning (Bachelor) - )

Module-ID: FIN-INF-110502
Link: LSF
Responsibility: Sebastian Stober
Lecturer: Sebastian Stober
Classes: Advanced Topics in Deep Learning 
Applicability in curriculum:

Abbreviation

Credit Points

5

Semester

every

Term

ab 1.

Duration

1 Semester

Language

english

Level

Bachelor

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

Type of examination: Teaching method / lecture hours per week (SWS):

  • Written report ("Hausarbeit")
  • Oral exam

Lecture/Seminar (2 SWS)

Prerequisites according to examination regulations: Recommended prerequisites:

none

Introduction to Deep Learning

Media: Literature:


Comments: