Artificial Intelligence, Systems, Data (IASD) - Master's Year 2

Program Year

UE obligatoires

  • Fondations of Machine Learning
  • Optimization for Machine Learning
  • Data acquisition, extraction and storage
  • Data Science Lab
  • Deep learning for image analysis
  • Reinforcement learning
  • Large language models

UE optionnelles

  • Advanced machine learning
  • Incremental learning, game theory and applications
  • Point Clouds and 3D Modelling
  • Knowledge graphs, description logics, reasoning on data
  • Graph analytics
  • Machine learning on Big Data
  • Computational social choice
  • Monte-Carlo search and games
  • Deep renforcement learning et applications
  • Privacy for Machine Learning
  • No SQL databases
  • Knowledge representation, planning and reasoning
  • Planning, search and constraint solving

UE Obligatoires

Academic Training Year 2024 - 2025 - subject to modification

Teaching Modalities

The IASD Master's program consists of a semester of advanced courses in AI disciplines (September to December), followed by a semester of options (January to April) and a research internship (April to September). Courses are divided into two semesters. During the first core semester, from September to December, students take six courses in artificial intelligence and data science. During the second semester of electives, from January to April, students must choose a minimum of six in-depth courses from a wide selection of options. The internship, from April to August, is carried out in an academic or industrial research laboratory and culminates in the writing of a dissertation and an oral presentation in September. For students who need it, refresher courses in mathematical and computer science fundamentals are scheduled before the start of the core curriculum in September.

The courses are taught by researchers active in the field, and cover the different aspects of AI today: machine learning, knowledge representation, management and mining of large masses of data, and Big Data paradigms. In addition to the core courses, students can customize their curriculum by choosing 6 additional courses from a wide range of options.

In semester 4, students enrolled in the 2nd year of the Master of Computer Science IASD program can choose optional courses from those offered in the 2nd year of the Master of Mathematics and Applications MASH program. This requires :

  • A written request from the student.
  • A written agreement from the teacher of the course concerned.
  • A written response from the administration.
  • Compliance with M2 MASH assessment procedures for the evaluation of UEs.

UE obligatoires

  • Fondamentaux de l’apprentissage automatique
  • Optimisation pour l'apprentissage automatique
  • Bases de données avancées (SBGD non classiques)
  • Apprentissage Profond
  • Systèmes, paradigmes et langages pour les Big Data
  • Ethique et science des données
  • Fouille de Graphes
  • Qualité des données
  • Traitement automatique des langues - NLP
  • Apprentissage par renforcement

UE obligatoires

  • Apprentissage profond pour l’analyse d’images
  • Flux de données
  • Recherche Monte-Carlo et Jeux
  • Visualisation de données
  • IA sur le Cloud
  • Projet Sciences des Données
  • Modélisation de problèmes
  • Machine Learning sur Big Data

UE obligatoires

Academic Training Year 2024 - 2025 - subject to modification

Teaching Modalities

The program starts in September and attendance is required. Students rotate between four weeks at a company and two or three weeks at the university.

The program is divided into two semesters, S3 and S4. Each semester is made up of a course, as well as a thesis in S4.
The final grade for a course is the cumulation of grades for continuous assessment, projects, homework, oral or written exams, and participation. Every course for which a student receives a final grade of 10/20 or above is deemed passed, and the appropriate ECTS credits are granted.

Each semester is made up of courses, as well as a thesis in S4. A student will have passed a semester if all the following conditions are met:

  • They take at least 30 ECTS Their final grade for the semester is at least 10/20
  • Their final grade for the semester is at least 10/20.
  • The final grade for each course taken that semester is at least 6/20
  • The final grade for the thesis in semester 4 is at least 10/20
  • If a student has passed a semester, they are to considered to have passed all the courses that make up that semester and to have received the associated ECTS credits.

To pass a year, the student must have passed both semesters and all the courses that make up that unit and to have received the associated ECTS credits. A student will have passed a year (and received the associated 60 ECTS credits) if all the following conditions are met:

  • They have taken at least 60 ECTS credits and receive a final grade for the year of at least 10/20
  • The final grade for each semester is at least 10/20
  • The final grade for each course in each semester is at least 6/20
  • The final grade for the thesis in semester 4 is at least 10/20


Internships and Supervised Projects

IASD Master's students must complete a 5-month internship, starting in April 2022.   List of internships available: here  For students: how to find an internship, and obtain the agreement. To find an internship, you can consult the list of internship offers, or approach the laboratories or companies that interest you yourself. Next, you'll need to obtain pedagogical approval for your internship subject. To obtain it, upload your subject here. Specify in the comments that the subject is for you. (Please do not send your subject by e-mail). Once you have obtained pedagogical validation, you can fill in the form in the ESUPstage application to obtain your internship agreement. For more information on the presentation of internships.   For supervisors: how to offer an internship to IASD Master's students? If you are part of a research laboratory or R&D department, you can propose an internship topic to students by clicking here. Of course, the internship must be related to one of the subjects covered in the Master's program. The internship will appear in the list below once it has been validated by the teaching staff.   Remuneration: In France, internships lasting more than 2 months must be gratified. Further information and a tool for calculating gratification for interns are available here: https://www.service-public.fr/simulateur/calcul/gratification-stagiaire.