Mathematics, Machine Learning, Sciences, and Humanities: Master's Year 2

Program Year

UE Introductifs obligatoires en statistiques bayésienne

  • Introduction à R
  • Introduction au Bayesian
  • A review of probability theory foundations
  • Introduction à Python

Cours fondamentaux

  • Optimisation pour l'apprentissage automatique
  • Optimisation
  • Statistiques en grandes dimensions
  • Modèles graphiques
  • Advanced learning

Cours optionnels - 5 cours à choisir parmi :

  • Transport optimal
  • Computational methods and MCMC
  • Applied bayesian statistics
  • Bayesian non parametric and Bayesian Machine Learning
  • Mixing times of Markov chains
  • Object recognition and computer vision
  • Journalisme et données
  • Natural language processing
  • Renforcement learning
  • Evaluations des politiques publiques
  • Méthode à noyau pour l'apprentissage

Mémoire de recherche

Academic Training Year 2023 - 2024 - subject to modification

Teaching Modalities

The program starts in September and attendance is required.

The program consists of a block of six required core courses in statistical machine learning. Students must pass four electives, including at least one from each unit, as well as a required internship of at least four months in duration in a company or research center.

Course information:

  • 24 courses and two required introductory courses in Bayesian statistics are offered: 16 at Paris Dauphine-PSL and 8 at ENS or MINES
  • All courses correspond to 4 ECTS credits, except for the two introductory courses, which are 0 credit courses
  • A student must pass 10 courses (the equivalent of 40 ECTS credits) including six required core courses and four electives.
  • Attendance is required at all courses in which a student is registered, and any absences will negatively affect the final grade.
  • If a student receives a final grade of at least 10/20 on the research thesis, they are considered to have passed the thesis and will receive 20 ECTS credits.

Internships and Supervised Projects

Students can choose between an internship suggested by a faculty member, an internship featured at the “Internship Fair,� or a different internship with the prior approval of the Master's program director. The internship must take place after enrollment in the Master's degree program. It should pose a solid research question and present an opportunity for the practical application of one of the themes examined over the course of the Master's program.
It should last at least four months, from April to September of the academic year in which it is to be taken. Except in very rare, preapproved cases, the internship must conclude by the end of September at the latest.