During my PhD, I had the opportunity to teach at the University of Lille. I was lucky to teach a Master’s course, with the freedom to design the lectures and tutorials. I created all of the lecture materials and tutorials myself.
As part of a Computer Science degree specialized in Machine Learning, the lecture aims to give students a better intuition for high-dimensional spaces and the trade-off between dimensionality reduction and preserving data characteristics. The goal is also to strengthen their mathematical background and their ability to code in Python. The lecture covers the curse of dimensionality, PCA, SVD, kernel-PCA, manifold learning, LLE, t-SNE, spectral clustering, and more.
I taught this lecture for three years.