Data Science

Advanced Algorithms for Machine Learning and Data Mining

A prior algorithms (Frequent item sets) & Page Rank Monte-carlo, MCMC methods: Metropolis-Hastings and Gibbs Sampling...

Advanced Imaging

In this course, we will first focus on linear methods for image denoising.

An introduction to shape and topology optimization

In a very broad acceptation, shape and topology optimization is about finding the best domain (which may represent, depending on applications, a mechanical structure, a fluid channel,…) with respect to a given performance criterion (e.g. robustness, weight, etc.), under some constraints (e.g. of a geometric nature).

Category learning and object recognition aka Machine learning for computer vision and audio processing

This course addresses advanced aspects of information access and retrieval, focusing on several points: ...

Computational biology

This interdisciplinary MSc course is designed for applicants with a biomedical, computational or mathematical background.

Data science seminar

This courses introduces probabilistic models with latent variables, and the associated algorithms to estimate the parameters and perform inference over the latent variables.

Efficient methods in optimization

Theoretical foundations of convex optimization.

Fundamentals of probabilistic data mining

This courses introduces probabilistic models with latent variables, and the associated algorithms to estimate the parameters and perform inference over the latent variables.

Geophysical imaging

Understanding Earth's interior mechanisms, assessing seismic hazard due to earthquakes and volcanoes, securing our access to hydrocarbon resources and monitoring CO2 storage sites, all represent crucial issues for modern societies.

GPU Computing

In this course, we will introduce parallel programming paradigms to the students in the context of applied mathematics.