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M2 S3: 2nd year, 3rd semester

All courses take place over 24 hours and are gathered in teaching units (UE=unit´s d'enseignement).

Teaching units


(decision of the teaching team) Welcome sessions: 1 or 2 intensive weeks of preparation/adaptation depending on the students background.


  • 24h Theory of machine learning
  • 24h Learning from big/tall data
  • 24h Kernel machines
  • 24h Sequential decision making/Reinforcement learning
  • 24h Graphs & networks
  • 24h Advanced methods for inference
  • 24h Distributed computing (Algorithmic 2)
  • 24h Machine learning for signal processing
  • 24h Advanced data bases
On top of courses, 4 important activities are:
  • Seminars (M1/M2)
  • Reading group
  • Kaggle competition 2
  • Research project

Internship: 16 weeks minimum (in a lab or company)

Head of Master program

Pierre Chainais-

Administration, secretary