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--- start [2025/10/27 09:43] – [Contacts] cxypolop
+++ start [2025/11/21 12:11] (current) – [Industrial & Institutional Partnership / Cercle des partenaires] director-llga
@@ Line 22: / Line 22: @@
 ==== Curriculum Description  ====
 The LLGA Master is a two-year program that combines a rigorous foundation with advanced specialization in Generative AI, focusing both on Large Language Models (LLMs) and graph-structured data.
+It will be followed by two training periods of 2.5 months, consisting of courses on the following topics **(detailed version [[https://msct.dix.polytechnique.fr/llga/wiki/doku.php?id=curriculum|here]])** :
+   * Large Language Models (LLMs) and Natural Language Processing (NLP)
+   * Graph Machine and Deep Learning
+   * Generative AI and Reinforcement Learning
 During the first year (M1), students build a strong academic basis through courses shared with engineering and other master’s programs at École polytechnique. This year develops solid skills in mathematics, machine learning, and deep learning, while also introducing key domains such as Natural Language Processing and Graph representation learning. By the end of the M1, students are equipped with the theoretical and methodological tools essential to pursue advanced AI studies.
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 Students are required to have a suitable background in mathematics and computer science. In practice, this means knowledge of linear algebra, statistics, as well as Python programming, algorithms and data structures. Some exposure to natural language processing and graph theory is desirable, but not required. Candidates with Bachelor degrees that are not in Mathematics or Computer Science are also admissible if the required knowledge domains are covered in their degree programs.
-==== Industrial & Institutional Partnership / Cercle des partenaires ====
+==== Professional and Industrial Placement / Placement Professionnel et Industriel des titulaires du MScT ====
-Students will have highly suitable profiles for data science or AI roles in industry. While the LLM aspect of the program allows students to apply to companies in most digital companies, the graphs and applications aspect of the program prepares the students particularly well for roles in the pharma, logistics and communication industries.  Graduates of the LLGA Master’s Program are prepared for careers as AI/ML Engineers, Data Scientists, NLP Specialists, Graph AI Experts, and AI Research Scientists, as well as strategic roles such as AI Product Managers, Solution Architect.  Opportunities span industries including tech, healthcare, finance, consulting, social media, e-commerce, and public institutions.
+Students will have highly suitable profiles for data science or AI roles in industry. While the LLM aspect of the program allows students to apply to companies in most digital companies, the graphs and applications aspect of the program prepares the students particularly well for roles in the pharma, logistics and communication industries.  Graduates of the LLGA Master’s Program are prepared for careers as AI/ML Engineers, Data Scientists, NLP Specialists, Prompt Engineers, Graph AI Experts, and AI Research Scientists, as well as strategic roles such as, Chief AI officers,  AI Product Managers, Solution Architect.  Opportunities span industries including tech, healthcare, finance, consulting, social media, e-commerce, and public institutions.
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 The academic directors of the MScT are:
+  * [[https://www.lix.polytechnique.fr/Labo/Michalis.Vazirgiannis/|Michalis Vazirgiannis]], Computer Science, Ecole Polytechnique [[michalis.vazirgiannis@polytechnique.edu]]
+  * [[https://remi.flamary.com/|Rémi Flamary]], Applied Mathematics, Ecole Polytechnique [[remi.flamary@polytechnique.edu]]
+The Associated Faculty are:
   * [[https://johanneslutzeyer.com/|Johannes Lutzeyer]], Computer Science, Ecole Polytechnique [[johannes.lutzeyer@polytechnique.edu]]
   * [[https://www.cmap.polytechnique.fr/~aymeric.dieuleveut/|Aymeric Dieuleveut]], Applied Mathematics, Ecole Polytechnique [[aymeric.dieuleveut@polytechnique.edu]]
-  * [[https://www.lix.polytechnique.fr/Labo/Michalis.Vazirgiannis/|Michalis Vazirgiannis]], Computer Science, Ecole Polytechnique [[michalis.vazirgiannis@polytechnique.edu]]
   * [[https://l-yezhu.github.io/|Ye Zhu]], Computer Science, Ecole Polytechnique [[ye.zhu@polytechnique.edu]]
-  * [[https://remi.flamary.com/|Rémi Flamary]], Applied Mathematics, Ecole Polytechnique [[remi.flamary@polytechnique.edu]]
   * [[https://luizchamon.com/|Luiz Chamon]], Applied Mathematics, Ecole Polytechnique [[luiz.chamon@polytechnique.edu]]