Teaching

Courses & Student Mentorship

Teaching at EPITA

I teach advanced courses in Artificial Intelligence and Deep Learning at EPITA School of Engineering. My teaching focuses on cutting-edge topics in machine learning and emerging paradigms.

I try to keep the courses practical and research-aware, so students do not only learn how to use a method but also when it is appropriate, what its limitations are, and how to evaluate it carefully. When possible, I connect lecture material to current papers, benchmark practices, and implementation choices that matter in real projects.

Deep Learning

Master's Degree ("Data Scicence, AI and Graphs, "Industry of the Future")

2024/25 - 2025/26

Advanced course covering modern deep learning architectures, optimization techniques, and practical applications. Topics include convolutional neural networks, recurrent networks, attention mechanisms, and transformers.

Research Elective: Benchmarking

Bachelor's Degree

2025/26

Provides the basics on benchmarking and introduction to scientific research.

Differential Programming Paradigm and Implementation

Master's Degree ("Data Scicence, AI and Graphs)

2025/26

Explores the paradigm of automatic differentiation and its applications in machine learning. Covers differentiation theory, implementation techniques, and modern frameworks for building differentiable systems.