École polytechnique campus

Engineering

MSc&T Large Language Models, Graphs and Applications (LLGA) at École polytechnique

École polytechnique, France

Programme overview

Two-year, fully English-taught master's specialisation in generative AI with an emphasis on large language models and graph-structured data (graph neural networks), applied to fields such as healthcare, biology and finance.

Faculty: Master of Science and Technology (MSc&T)  |  Duration: 2 years (140 ECTS)  |  Study mode: full-time; taught in English  |  Intake: September  |  Location: Palaiseau, Île-de-France, France

What you will study

Foundations in machine and deep learning plus hands-on work with generative techniques through projects, case studies and industry applications.

Career pathways

AI/ML engineer, data scientist, NLP specialist, graph AI expert, AI research scientist, AI product manager and solution architect roles in tech, healthcare, finance, consulting, social media, e-commerce and public institutions; PhD study is possible.

Official programme page

Application information

Entry requirements

Applicants enter M1 (bachelor degree) or M2 (master's degree or M1-level, 240 ECTS or more). English proficiency required: TOEFL iBT 95, IELTS Academic 7.0 or Cambridge Advanced C1, unless native speaker or last degree taught entirely in English; no French required. Four application rounds (2027 intake opens 16 September 2026), online application, admissibility jury then interview; application fee EUR 95. Prerequisites: knowledge of linear algebra, statistics, Python programming, algorithms and data structures; some exposure to natural language processing and graph theory is desirable but not required. Bachelor's degrees outside mathematics or computer science are admissible if these domains are covered.

EUR 15,500 a year. MSc&T annual tuition; EUR 12,500 per year for students from IP Paris and Bachelor of Science graduates of Ecole Polytechnique. Application fee (EUR 95) and non-refundable EUR 3,200 deposit (deducted from tuition) not included. Source

Intake: September

Duration: 2 years (140 ECTS)

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