Teaching

Regular Courses

[Spring 2023, 2024] CAPSTONE projects
Master 2 of Data Science ( M2DS ), Institut Polytechnique de Paris.
Projects between industrial mentors and Masters students. Reach out if you are an industrial and interested in mentoring a Data Science project for 2025 edition!

[Spring 2022, 2023, 2024] Emerging topics in Machine Learning (MAP 588)
for Polytechnique 3rd year students. Co-taught with Rémi Flamary.
[Moodle 2023] for students only.

[Fall 2021] Optimization and Computational Linear Algebra Graduate Course (DS-GA1014)
NYU Center for Data Science
[Course page].

[Spring 2021] Machine Learning Graduate Course, NYU CDS (DS-GA1003)
NYU Center for Data Science, co-taught with He He.
[Course website].

Doctoral School Lectures

[Sep 2022] Enhancing sampling of physical systems with learning
Physics meets AI, Arnold Sommerfeld School in Munich, Germany
[Event Link] [Slides] [Tutorial]

[June 2022] Enhancing sampling with learning: MCMC, generative models and overlaps
Flatiron Machine Learning X Science Summer School in New York, USA
[Event Link] [Slides]

[August 2021] Statistical mechanics of learning: the physicist’s view on learning theory
Summer School on Machine Learning in Quantum Physics and Chemistry in Warsaw, Poland. Thanks to the dedication of Anna Dawid, other organizers, students and lecturers, the lecture notes of this school were turned in a book!
[Book preprint] [Lecture slides]

[Feb 2020] Statistical physics for machine learning
Machine learning in physics, VDSP-ESI Winter School in Vienna, Austria
[Slides + Tutorial]

Divulgation

[Fall 2023, Spring 2024] L'apprentissage automatique: premiers pas vers l'IA
Programme Poincaré, École Polytechnique.
Cours d'introduction à l'apprentissage automatique niveau lycée. Ce cours prend l'exemple de la regression linéaire pour donner un exemple concret des mathématiques derrière l'IA, en initiant les étudiants à l'algèbre linéaire.
[Cours 1] [Cours 2] [Cours 3] [Cours 4]
[Page Moodle] pour les étudiants uniquement.

[March 2022, 2023] Bases mathématiques de l’apprentissage automatique ou Comment un ordinateur peut-il apprendre ?
Journée Filles, Maths et Informatique, École Polytechnique. [Slides]