Artificial Intelligence, Systems, Data - Mathematics Track - Master's Year 2

Syllabus

Cours obligatoires

  • Optimization for Machine Learning
  • Foundations of Machine Learning
  • Reinforcement learning
  • Data Science Lab
  • Large dimensional statistics
  • Optimal transport (ENS)
  • Bayesian inference

Cours optionnels - 5 cours à choisir parmi :

  • Computational statistics methods and MCMC
  • Bayesian machine learning
  • Graphical models
  • Dimension reduction and manifold learning
  • Non-convex inverse problems
  • Mixing times of Markov chains
  • Kernel methods
  • Large language models
  • Deep learning for image analysis
  • Data acquisition, extraction and storage

PSL Week

Bloc stage

Academic Training Year 2025 - 2026 - subject to modification


Teaching Modalities

From January 2025, classes will be held at 16 bis rue de l'Estrapade, 75005 Paris.

The program starts in September and attendance is required.


Internships and Supervised Projects

Students are free to choose an internship proposed by one of the teaching staff, a company internship offered through the "bourse des stages", or an internship of a different origin approved by the Master's supervisor. The internship must be carried out after registration for the Master's program. It must involve a real scientific challenge and the applicative development of one of the themes developed in the Master's program.
The minimum duration is four months, between April and September of the current academic year. Barring exceptional exception, the internship must be completed by the end of September at the latest.