Graphical models are probabilistic models that use a graph to represent the conditional dependence structure between random variables. They are used in probability theory, Bayesian statistics and machine learning. They allow for efficient computation of probabilities and inference.

It emphasizes inference in engineering settings, utilizing the powerful language of probabilistic graphical models. This course provides a good blend of probability theory, graph theory, and computation.