Home
The Master of Artificial Intelligence is jointly offered by UFR IM²AG, the Department of Informatics and Mathematics at Université Grenoble Alpes, and Ensimag, a school of engineering specializing in Applied Mathematics and Informatics of Grenoble INP.
The academic program is a highly competitive, two-year graduate program adhering to European standards (LMD), structured into Master 1 and Master 2 levels.
Organization of M1#
Master 1 is scheduled to commence in 2026.
Organization of M2#
The M2 program consists of two semesters: one semester of theoretical studies (semester S9) worth 30 ECTS, and one semester of internship (semester S10) lasting at least 18 weeks, also worth 30 ECTS.
Semester S9#
Semester S9 offers specialized training in two themes: Foundations and Advanced Methods in Machine Learning or Applied Artificial Intelligence and Interactive Systems. The courses and their descriptions are provided below. For this semester, students need to select:
- Courses worth 18 ECTS in their chosen theme and 12 ECTS of courses from the other theme or cross-disciplinary courses (provided below);
- Ensuring that timetables are consistent and enrollment restrictions apply.
| Theme I: Foundations and Advanced Methods in Machine Learning | Theme II: Applied Artificial Intelligence and Interactive Systems |
|---|---|
| Mathematical Foundations of Machine Learning (6 ECTS) | Natural Language Processing & Information Retrieval (6 ECTS) |
| Statistical Learning : from parametric to nonparametric models (6 ECTS) | Computer Vision (6 ECTS) |
| Mathematical Optimization (6 ECTS) | Human-Computer Interaction (6 ECTS) |
| Advanced Machine Learning: Applications to Vision, Audio and Text (6 ECTS) | Robotics (6 ECTS) |
| Learning, Probabilities and Causality (6 ECTS) | Computer Graphics (6 ECTS) |
| From Basic Machine Learning models to Advanced Kernel Learning (6 ECTS) | Large scale Data Management and Distributed Systems (6 ECTS) |
| Optimization under uncertainty (6 ECTS) | Information Visualization (3 ECTS) |
| Multi-agent systems (3 ECTS) |
| Cross-disciplinary courses |
|---|
| Explainable & Trustworthy AI (3 ECTS) |
| Scientific Methodology, Regulatory and ethical data usage (3 ECTS) |
| Optimized Management & Processing for learning (3 ECTS) |
| Advanced models and methods in operations research (6 ECTS) |
| GPU Computing (3 ECTS) |
Semester S10#
The final semester (S10) is dedicated to an individual Master's research or professional project conducted in industry, under the supervision of an advisor in the company and an academic tutor, or at a public research laboratory, under the supervision of an academic advisor.
A professional project requires an industry-grade design and implementation and is evaluated based on the professional quality of the design, specification, documentation, and performance evaluation or acceptance tests.
A scientific research project requires an original solution to a problem within an existing scientific domain. The project will be evaluated based on the mastery of the scientific state of the art, depth of analysis and understanding of the problem, originality of the proposed solution, and quality of the validation or experimental performance evaluation. Continuation to doctoral studies requires demonstrating aptitude for scientific research by completing a scientific research project.
