Courses

This page brings together a curated set of three courses exploring the interplay between random networks and learning. From the foundations of probabilistic graph models to modern approaches in machine learning on networked data, these courses are designed to guide the interested students through both theory and practice. These courses were delivered as part of the Workshop on Randomness and Learning on Networks at IMPA, organized by RandNET. They are intended for researchers from other areas who have a background in basic mathematics, such as calculus, algebra, and probability.