Composition du parcours
- DS-ENSAE-1 Statistical Learning Theory
- MAP670U Monte Carlo Methods: from MCMC to Data -based Generative Model
- DS-ECE-1 Big Data Framework
- DS-ENSAE-4 Estimation non paramétrique en Nonparametic estimation and testing
- DS-ENSAE-2 High dimentional statistics
- DS-télécom-7 Convex Analysis and Optimization Theory
- MAP654I Practical introduction to machine learning
- DS-télécom-6 Deep Learning 1
- DS-télécom-8 An introduction to Machine Learning Theory
- DS-télécom-20 Natural Language Processing
- DS-ENSAE-3 Hidden Markov models and Sequential Monte Carlo methods
- MAP670N Advanced Learning for text and graph Data
- MAP670L Generalisation properties of algorithms in ML
- MAP670H High-dimensional Matrix Estimation
- DS-télécom-11 Modèles de Markov partiellement observés en signal et image
- MAP670P Law and ethics of artificial intelligence
- DS-télécom-1 Optimization for Data Science
- MAP670C Reinforcement Learning (M2DS)
- DS-télécom-13 Deep Learning for Computer Vision
- MAP670G Data Stream Processing
- DS-ENSTA-2a Introduction à la Recherche opérationnelle et données massives class="parent_li" role="treeitem"> M2DS - S1 - Electifs H.M. M2DS - Semestre 1 - Electifs hors maquette
