The course will give students an overview of selected topics in advanced machine learning that are currently subjects of active research. The course concludes with a final project.

The course will cover: Random experiments, sample spaces, events| Probability measures| Conditional probability, Bayes rule.| Independence| Random variables (discrete & continuous) and their distributionfunction, Well-known distributions| Joint distributions| Expectation and variance| Covariance and correlation| Conditional expectation,Modes of convergence.