M2 Traitement de l'information et exploitation données

Master's degree
Electronique, Energie Electrique, Automatique
Full-time academic programmes
French

Expert in data analysis and modeling. Mastery of artificial intelligence (AI) concepts and technologies.

A five-week project within one of the partner laboratories is offered. The objective is to implement learning methods on a project proposed by a team of researchers from the laboratory. It is also an opportunity for some to consider pursuing a PhD.

Information

Présentation

Objectives

The TRIED Master's degree trains data scientists who are experts in data analysis, processing, and modeling. They master the concepts and technologies of artificial intelligence (AI). The training is multidisciplinary, at the crossroads of applied mathematics, computer science, and physics. The objective is to acquire the skills necessary to develop machine learning algorithms for complex statistical modeling in various application fields. The training also allows students to pursue a thesis, particularly in one of the partner laboratories. The training of engineers or future researchers in data analysis and modeling is based on a balance between theoretical and practical training. In-depth knowledge of the models is combined with learning how to implement them. All of the educational content and knowledge assessments offered emphasize teamwork, project work, the acquisition of cross-disciplinary skills, and the ability to implement skills from several disciplines. The master's degree is also co-accredited with the Telecom Sud Paris (TSP) engineering school of the Institut Polytechnique de Paris (IPP).

Career Opportunities

Career prospects

Après un Master ou Master + Doctorat : chercheur ou enseignant-chercheur
Ingenieur R&D
ingénieur étude conception
Consultant
Ingénieur d’études dans les domaines de l’industrie
Ingénieur d’études dans les domaines de la recherche
Ingénieur d'études industrie / recherche publique
Enseignants-chercheurs

Further Study Opportunities

domaines de l’apprentissage statistique, de l’intelligence artificielle ou de l’analyse de données avancée
ngénierie études, recherche et développement
Thèse de doctorat

Fees and scholarships

The amounts may vary depending on the programme and your personal circumstances.

Admission

Capacity

Available Places

18

Target Audience and Entry Requirements

The TRIED master's degree can be pursued either after completing a scientific Master 1 (Computer Science, Physics, Applied Mathematics, Statistics, Engineering Sciences, Electrical Engineering (E3A), English-language M1 in TSP), or after obtaining an engineering degree. The program can also be accessed by students in their final year of engineering school as part of an educational agreement or dual degree program (ISTY, TSP, ENSIIE, ESME, IPSA, etc.). Knowledge of statistical methods, probability, and signal processing is highly recommended. A good knowledge of a programming language (preferably Python) is also an advantage.

Application Period(s)

Inception Platform

From 01/03/2026 to 06/07/2026

Supporting documents

Compulsory supporting documents

Motivation letter.

All transcripts of the years / semesters validated since the high school diploma at the date of application.

Certificate of French (compulsory for non-French speakers).

Curriculum Vitae.

Additional supporting documents

VAP file (obligatory for all persons requesting a valuation of the assets to enter the diploma).

The application procedure, which depends on your nationality and your situation is explained here : https://urlz.fr/i3Lo.

Supporting documents :
- Residence permit stating the country of residence of the first country
- Or receipt of request stating the country of first asylum
- Or document from the UNHCR granting refugee status
- Or receipt of refugee status request delivered in France
- Or residence permit stating the refugee status delivered in France
- Or document stating subsidiary protection in France or abroad
- Or document stating temporary protection in France or abroad.

Programme

The schedule will be posted shortly.

Teaching Location(s)

PARIS 03
PALAISEAU

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