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).

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

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 (6 ECTS, 30 max).

Convex Analysis and Optimization Theory (6 ECTS).

DATA stream processing (6 ECTS, 70 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).

Natural Language Processing and Sentiment Analysis (6 ECTS, 60 max).

Nonparametic estimation and testing (3 ECTS).

Optimization for Data science (6 ECTS).

Statistical Learning Theory (3 ECTS, 50 max).

Generalisation properties of algorithms in ML (6 ECTS, 40 max).

Part 2 (November-January):

Deep learning for Computer Vision (3 ECTS).

Operator Learning, applications in dynamical systems and uncertainty quantification (3 ECTS, 30 max).

Introduction to Generative models (3 ECTS).

Introduction to Operation Research (3 ECTS).

Law and ethics of artificial intelligence (3 ECTS).

Partially observed Markov chains in signal and image (French) (3 ECTS).

Reinforcement learning (3 ECTS).

Part 3 (January-March):

Audio and music information retrieval (6 ECTS).

Big Data and Insurance Project (3 ECTS, 30 max).

Causal inference (3 ECTS, 40 max).

Cloud data infrastructure (3 ECTS, 40 max).

Cooperative Optimization for Data Science (3 ECTS).

Deep Learning II (3 ECTS).

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

Online learning and aggregation (3 ECTS).

Integer Optimization for Machine Learning (3 ECTS).

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, outliers and models for extreme (3 ECTS).

M2DS IP Paris, courses selection simulation