MScT LLGA

Programme of the Master of Science and Technology (MScT) of Ecole Polytechnique

Link to the official page on the Ecole Polytechnique website.

The LLGA Master’s Program is a two-year, fully English-taught degree with a strong international outlook. Designed for ambitious students, the program equips graduates with both a solid theoretical foundation and hands-on industry expertise in Generative AI. With a special emphasis on Large Language Models (LLMs) and graph-structured data, students gain the skills to harness cutting-edge technologies and apply them across diverse fields—from healthcare and biology to finance, social networks, and beyond.

In recent years, Generative AI has seen explosive growth, with Large Language Models (LLMs) reshaping how society and the economy interact with the digital world. These technologies enable tasks that were unimaginable just a few years ago—from machine translation and code generation to creative content generation and advanced reasoning —at unprecedented scale. The objective of the LLGA Master’s Program is to prepare students to become experts in this transformative field, with the skills to advance both theory and application. Equally important are graph-based data and models, which capture the structure of complex relationships in social networks, molecular structures, or logistics chains. Advances in Graph Neural Networks (GNNs) and Graph Representation Learning are unlocking insights and applications previously out of reach. Combining LLMs with graph-based methods enables multimodal generative AI, opening new opportunities in healthcare, finance, recommendation systems, and beyond.

The goal of the LLGA program is to provide students with a solid theoretical foundation in machine and deep learning, alongside hands-on experience with state-of-the-art generative techniques in the context of LLMs and graph generation. Through projects, case studies, and industrial applications, graduates acquire rare and highly sought-after expertise, positioning them to innovate and lead in the next generation of AI technologies.

Courses are given by professors from Ecole Polytechnique and partner institutes and companies.

All courses will be held in English. Both French and foreign students are welcome.

The first week consists of refresher courses in mathematics (statistical analysis, introduction to Machine Learning) and Computer Science (C++ programming, basics of 3D modeling and algorithmic geometry), to complement the existing academic background of the students.

It will be followed by two training periods of 2.5 months, consisting of courses on the following topics (detailed version here) :

• Deep Learning, Generative AI and Reinforcement learning
• Geometric data analysis and deep learning on such data
• AI in Computer Graphics, Virtual and Augmented Reality
• AI on sequence data including text (LLMs)
• Computer vision (images-based 3D reconstruction, recognition in images & videos)
• Robotics from motion planning to the design of soft robots for medical applications

In complement, a weekly seminar will encourage discussions of ethical issues and novel applications, while transverse projects will give some practical, real-world experience to each student in one or several domains of interest.

The last part of the school year will consist of a five- to six-month research project, conducted either in a public or private research lab.

We are looking for very strong students with initial high-quality training in either Computer Science or Applied Mathematics.

Please take a look at the official documentation for application process details.

Our MScT is accompanied by an active group of industrial and institutional partners contributing both student grants and transverse projects, as well as student internships. Some in the past, some currently, these partners include Inria, Google, Enedis, Idemia, Helsing as well as, younger companies such as Anatoscope, Homiwoo, InitML and Wemap.

Students have the option to either find their own internship position or to choose one of the internship proposals that we have made available here and are regularly updating.

The academic co-directors of the MScT are:

• Johannes Lutzeyer, Computer Science (LIX / DIX), Ecole Polytechnique johannes.lutzeyer@polytechnique.edu
• Aymeric Dieuleveut, Applied Mathematics (CMAP), Ecole Polytechnique aymeric.dieuleveut@polytechnique.edu
• Michalis Vazirgiannis, Computer Science (LIX / DIX), Ecole Polytechnique michalis.vazirgiannis@polytechnique.edu
• Ye Zhu, Computer Science (LIX / DIX), Ecole Polytechnique ye.zhu.lix@polytechnique.edu
• Rémi Flamary, Applied Mathematics (CMAP), Ecole Polytechnique remi.flamary@polytechnique.edu
• Luiz Chamon, Applied Mathematics (CMAP), luiz.chamon@polytechnique.edu

Please don't hesitate to contact us!