Fundamentals of Machine Learning (30h, Wed am from 6/12, Valrose): 
This course offers an in-depth look at some fundamental mathematical concepts driving recent advances in machine learning. 
Core topics encompass the theory of deep learning, large-scale and distributed optimization, causal inference, fairness, and safety in AI.

 Each topic will be explored through rigorous mathematical development complemented by practical Python-based experiments. 
For the final assessment, students must present a topic of their choice from a provided list and resources, following the same format of 
rigorous mathematical exploration and Python experimentation.
