Semester Schedule

M1: Week 36-38

Topics

• W 36: Data Manipulation, Exploratory Data Analysis (EDA), Data Visualization
• W 37: Unsupervised Machine Learning (UML), Supervised Machine Learning (SML)
• W 38: Workshop & project work

M2: Week 39-41

Topics

• W 39: Introduction to Network Analysis
• W 40: Introduction to Natural-Language-Processing (NLP)
• W 41: Workshop & project work

M3: Week 43-46

Topics

• W 43: Introduction to Artificial Neural Networks (ANN) & Deep Learning (DL)
• W 44: Neural networks for spatial data: Recurrent Neural Networks (RNN)
• W 45: Neural Networks for sequential data: Recurrent Neural networks (RNN & LSTM)
• W 46: Workshop & project work

Key Dates

• In-person workshops on CBS campus (mostly Thursday + Friday)

  • 1: W38: Machine learning case studies
  • 2: W41: Advanced applications in Network and Text Analysis
  • 3: W46: Advanced applications & outlook in deep learning

• Individual assignment (2 out of 3 need to be passed):

  • 1: 23.-28.09.2022, 23:59:00 at the latest (Peergrade)
  • 2: 14.-26.10.2022, 23:59:00 at the latest (Peergrade)
  • 3: 14.-16.11.2022, 23:59:00 at the latest (Peergrade)

• Final exam (individual exam of group project)

  • Hand-out: 18.11.2022
  • Hand-in: 01.12.2021
  • Final exam: 16.12.2021