Actualités

M2 Mathematics and Artificial Intelligence is designed as a continuation of M1 Mathematics and Artificial Intelligence.

It is supported by the Mathematics department of Orsay and Centrale-Supelec, with the support of the computer science department and the SaclAI-school program.

Présentation

Mathematics plays an important role in artificial intelligence (AI), and in particular in learning. Data sciences, which combine mathematical modeling, statistics, computer science, visualization and applications, aim to move from the storage and dissemination of information to the creation of knowledge.

This transition from data to knowledge requires an interdisciplinary approach that relies heavily on the statistical processing of information (mathematical statistics, numerical statistics, statistical learning or machine learning).

The large dimension encourages the use of new tools from different branches of mathematics (functional analysis, numerical analysis, convex and non-convex optimization) which must be understood.

M2 Mathematics and AI allows students to master the mathematical issues and techniques that underpin machine learning, while providing solid computer skills for the development of projects in learning, data science and AI.

Organisation

M2 Mathematics and AI combines theoretical and methodological courses supplemented by “real-life” projects involving all aspects of data science, from acquisition to exploitation and analysis. A significant part of the course is validated in the form of projects.

The training ends with an internship of at least four months, generally beginning on April 1st. This internship must present a real scientific challenge and receive the approval of a master’s teacher.

Program

M2 Mathematics and Artificial Intelligence is structured in three course periods (September to early November, early November to mid-January, mid-January to late March). The period from early April to late September is reserved for the internship.

Its program offers compulsory modules and optional modules. Depending on the modules, the courses take place at the Orsay mathematics laboratory, at CentraleSupelec or the Paris-Saclay computer science laboratory.

The optional modules are designed to allow the student to choose their cursor between a very mathematical program and a more applied program: 

  syllabus 

After the master

There is currently a high demand of very "high-level" engineers in data sciences in both start-ups and large companies. These new "data scientist" professions are multifaceted, ranging from the implementation of new generations of decision-making information systems to the development of completely new applications (around e-commerce, recommendations, social network mining, etc.). The need for doctoral students is also significant in this field of disruptive innovations. Thesis proposals are numerous in public research (University, CNRS, INRIA, CEA, CNES, INRA, INSERM, LETI, etc.) and in large research laboratories in industry (Aerospace, Alcatel, Orange, Sagem, General Electric, Matra, Philips, Siemens, Thales, EDF, etc.).