Course unit, curriculum year 2026–2027
DATA.ML.230
Advanced Deep Learning, 5 cr
Tampere University
- Description
- Completion options
Teaching periods
Active in period 3 (1.1.2027–7.3.2027)
Course code
DATA.ML.230Language of learning
EnglishAcademic year
2026–2027Level of study
Advanced studiesGrading scale
General scale, 0-5Persons responsible
Responsible teacher:
Alexandros IosifidisResponsible organisation
Faculty of Information Technology and Communication Sciences 100 %
Coordinating organisation
Computing Sciences Studies 100 %
Content
- Advanced deep neural network architectures
- Deep neural network learning paradigms
- Deep neural networks for graphs
- Generative deep neural networks
- Implementations in Python (using PyTorch)
Learning outcomes
Prerequisites
Compulsory prerequisites
Further information
Learning material
Studies that include this course
Completion option 1
Exercises and exam
All parts of the completion option are compulsory.
Participation in teaching
Contact teaching
11.01.2027 – 28.02.2027
Active in period 3 (1.1.2027–7.3.2027)
Exam
No scheduled teaching