Bloc fondamental 1

• Algorithmic and advanced programming (5 ECTS)

• Anglais 1 (2 ECTS)

• Artificial Intelligence (3 ECTS)

• Graph theory (5 ECTS)

• Mathematics for data science (5 ECTS)

UE Complémentaires

• Décision collective, décision multicritère (5 ECTS)

• Game theory (5 ECTS)

• Programmation objet avancée (5 ECTS)

• Système et algorithmes répartis-SAR (5 ECTS)

Bloc fondamental 2

• Anglais 2 (2 ECTS)

• Combinatorial optimization (5 ECTS)

• Computer ethics & data protection (1 ECTS)

• Data base management system (5 ECTS)

• Machine Learning (5 ECTS)

UE Complémentaires

• Decision under uncertainty (5 ECTS)

• Logic theory (5 ECTS)

• ML Project/Data science (5 ECTS)

Bloc stage

• Stage (4 ECTS)

Fundamental Courses

• Graphs and applications (3 ECTS)

• Mathematical Programming (3 ECTS)

• Modelling in Decision Aiding - Operational Research (3 ECTS)

• Preference Modelling and Multiple Criteria Decision Making (3 ECTS)

• Industrial and design models (3 ECTS)

Optional courses (choose 5)

Courses for the Decision Stream

• Decision under uncertainty and decision models (3 ECTS)

• Multiobjective Optimization (3 ECTS)

• Robustness in Operations Research and Decision Aiding (3 ECTS)

• Algorithmic Decision Theory and Computational Social Choice (3 ECTS)

• Problem structuring methods (3 ECTS)

• Theory and practice of production scheduling (3 ECTS)

• Programmation par contraintes et applications (3 ECTS)

Courses for the Combinatorial Optimization Stream

• Complexity Theory (3 ECTS)

• Structural and algorithmic graph theory (3 ECTS)

• Approximation algorithms (3 ECTS)

• Geometric Aspects of Discrete Optimization (3 ECTS)

• Algorithmic games (3 ECTS)

• Stochastic programming (3 ECTS)

• Machine learning for optimization (3 ECTS)

• Algorithms for continuous optimization (3 ECTS)

• Exact algorithms for NP-complete and hard problems (3 ECTS)

Courses for the Organisation Stream

• Operations Research applied to environment and health systems (AgroParisTech) (3 ECTS)

• Gouvernance d'entreprise et innovation responsable (3 ECTS)

• Conception et dynamique des organisations (École des Mines) (3 ECTS)

Major research workshop - 20 ECTS (choose 1)

• Decision aiding : procedures, models and approaches (20 ECTS)

• Artificial Intelligence and Decision (20 ECTS)

• Mathematical Programming (20 ECTS)

• Algorithms with performance guarantee (20 ECTS)

• Modèles de gestion et dynamique des organisations (École des Mines) (20 ECTS)

Minor research workshop - 10 ETCS (choose 2)

Research workshops for the Decision Stream

• Decision aiding : procedures, models and approaches (5 ECTS)

• Artificial Intelligence and Decision (5 ECTS)

Research workshops for the Combinatorial Optimization Stream

• Mathematical Programming (5 ECTS)

• Algorithms with performance guarantee (5 ECTS)

Research workshops for the Organisation stream

• Modèles de gestion et dynamique des organisations (École des Mines) (5 ECTS)

Research Seminars

• Optimization Algorithms and Models : theory and applications (0 ECTS)

• Preference modelling and multiple criteria decision making (0 ECTS)

UE fondamentales 3

• Data acquisition, extraction and storage (4 ECTS)

• Data Science Lab (4 ECTS)

• Deep learning for image analysis (4 ECTS)

• Foundations of Machine Learning (4 ECTS)

• Large language models (4 ECTS)

• Optimization for Machine Learning (4 ECTS)

• Reinforcement learning (4 ECTS)

UE optionnelles (5 UE à choisir)

• Advanced machine learning (4 ECTS)

• Bayesian case studies (4 ECTS)

• Bayesian machine learning (4 ECTS)

• Bayesian statistics (4 ECTS)

• Computational social choice (4 ECTS)

• Computational statistics methods and MCMC (4 ECTS)

• Dimension reduction and manifold learning (4 ECTS)

• Graph analytics (4 ECTS)

• High-dimensional statistics (4 ECTS)

• Incremental learning, game theory and applications (4 ECTS)

• Introduction to causal inference (4 ECTS)

• Knowledge graphs, description logics, reasoning on data (4 ECTS)

• LLM for code and proof (4 ECTS)

• Machine learning on Big Data (4 ECTS)

• Machine learning with kernel method (4 ECTS)

• Mathematics of deep learning (4 ECTS)

• Monte-Carlo search and games (4 ECTS)

• Non-convex inverse problems (4 ECTS)

• NoSQL databases (4 ECTS)

• Optimal transport (4 ECTS)

• Point cloud and 3D modelling (4 ECTS)

• Topics in trustworthy machine learning (4 ECTS)

PSL Week - 2 ECTS (2 ECTS )

• PSL Week ( ECTS)

Bloc stage - 10 ECTS

• Stage (10 ECTS)

UE fondamentales

• Apprentissage par renforcement (3 ECTS)

• Apprentissage Profond (3 ECTS)

• Apprentissage topologique (3 ECTS)

• Bases de données avancées (SBGD non classiques) (3 ECTS)

• Ethique et science des données (1.5 ECTS)

• Fondamentaux de l’apprentissage automatique (3 ECTS)

• IA générative (3 ECTS)

• Optimisation pour l'apprentissage automatique (3 ECTS)

• Systèmes, paradigmes et langages pour les Big Data (3 ECTS)

• Traitement automatique des langues - NLP (3 ECTS)

UE fondamentales

• Apprentissage profond pour l’analyse d’images (3 ECTS)

• Flux de données (3 ECTS)

• IA sur le Cloud (3 ECTS)

• Machine Learning sur Big Data (3 ECTS)

• Modélisation de problèmes (3 ECTS)

• Projet Sciences des Données (3 ECTS)

• Recherche Monte-Carlo et Jeux (3 ECTS)

• Visualisation de données (3 ECTS)

Bloc mémoire - 7,5 ECTS

• Memoire (7.5 ECTS)