This course is designed for students with a background in communication systems and information theory, interested in doing research in machine learning. The first half of the course will focus on one-shot approaches in multiuser information theory and discuss some applications to machine learning. The second half will develop information theoretic bounds on the generalization error in statistical learning. The final course project is expected to be on a topic at the intersection of information theory and machine learning.