Teaching

Teaching (2023 - 2024)

Master 1: Agility
- Lecture: PDF file
- Pratical works:
  - TP0: Git introduction
  - TP1: Continuous integration
  - TP2: Forest simulator (unit tests)
  - TP3: Forest simulator (TDD)
  - TP4: Forest simulator (TDD + quality metrics)
  - TP5: Interface testing
  - TP7: Behavioral Driven Development

Master 1: Machine learning
- Lecture: PDF file
- Tutorials:
  - TD1: Decision tree
- Pratical works:
  - TP0: Python for ML introduction
  - TP1: Linear and Polynomial regression
  - TP2: KNN
  - TP3: K-means
  - TP4: Upper Confidence Bound
  - TP5: Q-learning
  - TP6: Neural Network (available later)
  - TP7: Convolutional Neural Network (available later)
  - …
- Projects:
  - Intermediate: supervised learning
  - Final project: advanced ML problem (available later)

BUT3: Deep learning
- Lecture: PDF file
- Pratical works:
  - TP1: Gradient descent
  - TP2: Deep Neural Network
  - TP3: Convolutional Neural Network (available later)
  - TP4: AutoEncoder (available later)
  - TP5: Generative Adversarial Network (available later)

Other resources:
- Configure Python: virtual environment
- Python: OOP and library main concepts