List of courses by tracks

1st year

APM_1S003_EP (MAA103) : Discrete Mathematics, Guillaume Dujardin, Houssna Zidani
APM_1S006_EP (MAA106) : Introduction to Numerical Analysis, Maxime Breden
APM_1S007_EP (MAA107) : Mathematical Modeling, Fabrice Djete

2nd year

APM_2F005_EP (MAA205) : Algorithms for Discrete Mathematics, Lucas Gerin
APM_2F010_EP (MAA210) : Probability and Statistics, JM Bardet, Yoan Tardy
APM_2S051_EP (MAA251) : Num Anal. 2: Linear Algebra and Optimization, Beniamin Bogosel, Teddy Pichard

3rd year

APM_3F004_EP (MAA304) : Asymptotic Statistics, Eric Moulines
APM_3F005_EP (MAA305) : Probability : stochastic processes, Quentin Cormier
APM_3F007_EP (MAA307) : Convex optimization and Optimal control, Anne Auger
APM_3F008_EP (MAA308) : Image analysis : Registration, Andres Almansa
APM_3S012_EP (MAA312) : Numerical Methods for ODEs, Michaël Goldman
FMA_3F013_EP (MAA313) : Seminar : Mathematical Models, Maxime Breden

Bachelor Thesis, Mazyar Mirrahimi

For further information on Bachelor Program

1st year

APM_3X061_EP (MAP361) - Randomness, Emmanuel Gobet

This course introduces the basic notions of probability theory, that is the mathematical analysis of phenomena in which chance occurs. The teachers will insist in particular on the two major notions which are the foundations of this theory : conditioning and the law of large numbers.

The teaching aims at the acquisition of probabilistic reasoning and the learning of probabilistic modeling and simulation, as it is fundamental in many applications. The course is illustrated by examples and numerical experiments. It also introduces some notions of measure theory and it offers an opening towards statistics. During this teaching, the students will carry out a simulation project in pairs.

2nd year

Period 1 (september to november)

APM_41012_EP (MAP412) - Introduction to Numerical Analysis: from mathematical foundations to experimentation with Jupyter, Marc Massot
APM_42031_EP (MAP431) - Analyse variationnelle des équations aux dérivées partielles, Philippe Moireau
APM_41033_EP (MAP433) -Statistiques, Eric Moulines
APM_41M01_EP (MAP471A) - Modal - Problem solving in applied mathematics, Lucas Gerin, Teddy Pichard

Period 2 (december to february)

APM_42031_EP (MAP431) - Variational analysis of partial differential equations, Philippe Moireau
APM_42032_EP (MAP432) - Modelling of random phenomena, Cyril Marzouk
APM_42M01_EP (MAP472A) - Modal - Mathematical modelling through the experimental approach, Beniamin Bogosel

Periode 3 (march to may)

APM_43035_EP (MAP435) - Optimization and control, Grégoire Allaire
APM_43M01_EP (MAP473B) - Modal - Dynamic systems, applications and simulations, Eric Gourdin
APM_43M02_EP (MP473D) - Modal - Random numerical simulation around rare events, Gersende Fort

3rd year

Period 1 (september to december)

APM_51050_EP (MAP550) - Théorie des jeux, Charles Bertucci
APM_51051_EP (MAP551) - Dynamic systems for modelling and simulation of multi-scale reactive media, Marc Massot
APM_51052_EP (MAP552) - Stochastic Models in Finance, Huyên Pham
APM_51053_EP (MAP553) - Foundation of Machine Learning, Erwan Le Pennec
APM_51055_EP (MAP555) - Signal processing, Rémi Flamary
APM_51056_EP (MAP556) - Monte Carlo methods, Alain Durmus
APM_51057_EP (MAP557) - Operational research: mathematical aspects and applications, Stéphane Gaubert
APM_51175_EP (MAP575) - EA - Advanced probability topics, Igor Kortchemski
APM_5117_EP (MAP576) - EA - Learning theory, Matthieu Lerasle, Laurent Massoulié
APM_51178_EP (MAP578) - EA - Emerging Topics in Machine Learning P1, Aymeric Dieuleveut, El Mahdi El Mhamdi

Period 2 (january to march)

APM_52062_EP (MAP562) - Optimal design of structures, Beniamin Bogosel
APM_52063_EP (MAP563) - Random modelling in biology, ecology and evolution, Vincent Bansaye
APM_52064_EP (MAP564) - Social and communication networks: probabilistic models and algorithms, Laurent Massoulié
APM_52065_EP (MAP565) - Random and statistical process modelling, Mathieu Rosenbaum
APM_52066_EP (MAP566) - Statistics in action, Zacharie Naulet
MDC_52067_EP (MAP567/MAT567) - Transport et diffusion, Teddy Pichard, François Golse, Gaël Raoul
APM_52068_EP (MAP568) - Uncertainty management and risk analysis, Josselin Garnier
APM_52069_EP (MAP569) - Regression and classification, Karim Lounici
APM_52183_EP (MAP583) - EA - Deep learning from theory to practice, Kevin Scaman
APM_52009_EP - ML for scientific computing , Hadrien Montanelli, Samuel Kokh, Loïc Gourin
MAP583 - EA (APM_52183)_EP - A Apprentissage profond, Kevin Scaman
MAP588 - EA (APM_52188)_EP - Emerging Topics in Machine Learning P2, Rémi Flamary

Period 3 (april to august): research internship

APM_52992_EP (MAP592) - Modelling and scientific computing, Ludovic Goudenège
APM_52993_EP (MAP593) - Automation and Operational Research, Stéphane Gaubert, Frédéric Meunier
APM_52994_EP (MAP594) - Probabilistic and statistical modelling, Aymeric Dieuleveut, Lucas Gerin
APM_52995_EP (MAP595) - Financial mathematics, Eduardo Abi Jaber, Charles-Albert Lehalle et Huyên Pham

Data Science for Business - X and HEC, Erwan Le Pennec
Data Science for Finance - X and HEC, Stefano de Marco
Artificial Intelligence & Advanced Visual Computing, Simsekli Umut

Some courses have benefited from a government grant managed by the ANR under France 2030 with the reference "ANR-22-CMAS-0002"

Applied Mathematics and Statistics

M1 Applied Mathematics and statistics, Clément Rey
M2 Data Science, Rémy Flamary, El Mhamdi El Mahdi
M2 Mathematical modelling, Grégoire Allaire
M2 Probability and Finance, Huyên Pham

Some courses have benefited from a government grant managed by the ANR under France 2030 with the reference "ANR-22-CMAS-0002"

Mathematics and Applications

M2 Mathematics of Randomness, Matthieu Lerasle
M2 Mathematics for Life Sciences, Sylvie Méléard
M2 Mathematics, Vision, Learning, Josselin Garnier
M2 Optimization, Stéphane Gaubert