M2DS IP Paris, courses selection form

ENSAE or ENSTA double diploma student (courses from school, 10 ECTS)

Part 1 (September-October):

An Introduction to Machine Learning Theory (3 ECTS, 60 max).

Deep Learning I (3 ECTS).

Monte Carlo methods and approximate inference (3 ECTS, 30 max).

Practical introduction to machine learning (3 ECTS, 60 max).

Part 1-2 (September-January):

Advanced AI for text and graphs (6 ECTS, 45 max).

Big Data Framework (3 ECTS, 30 max).

Convex Analysis and Optimization Theory (6 ECTS).

DATA stream processing (6 ECTS, 70 max).

Optimization Meets Generalization: Insights from Statistical and Neural Network Learning (6 ECTS, 40 max).

Hidden Markov models and Sequential Monte Carlo methods (3 ECTS).

High-dimensional statistics (3 ECTS, 15 max).

Machine Learning for Climate and Energy (3 ECTS, 20 max).

Nonparametic estimation and testing (3 ECTS).

Optimization for Data science (6 ECTS).

Online learning and aggregation (3 ECTS).

Part 2 (November-January):

Deep learning for Computer Vision (3 ECTS).

Kernel Machines: from shallow to deep learning (3 ECTS, 60 max).

Introduction to Generative models (3 ECTS).

Introduction to Operation Research (3 ECTS).

Law and ethics of artificial intelligence (3 ECTS).

Machine Learning Structured Data (3 ECTS).

Natural Language Processing and Large Language Models (3 ECTS, 80 max).

Reinforcement learning (3 ECTS).

Part 3 (January-March):

AI for Sound : Analysis Processing and generation (6 ECTS).

AI Driven Transformation (3 ECTS, 30 max).

Cloud data infrastructure (3 ECTS, 40 max).

Cooperative Optimization for Data Science (3 ECTS).

Deep Learning II (3 ECTS).

Deep learning for time series (3 ECTS, 50 max).

Generative models for visual content prediction (3 ECTS).

Integer Optimization for Machine Learning (3 ECTS).

Introduction to eXplainable ArtificiaI Intelligence : interpretable models, post-hoc explanability and causality (3 ECTS, 40 max).

Machine Learning with Graphs (3 ECTS, 50 max).

Optimal Transport: Theory, Computations, Statistics, and ML Applications (3 ECTS).

Recent Developments in Responsible AI (3 ECTS, 50 max).

Representation Learning for Computer Vision and Médical Imaging (3 ECTS).

Stochastic approximation and reinforcement learning (3 ECTS).

Tail events analysis: robustness and anomaly detection (3 ECTS).