This is the second course in a two-course sequence on Large-Scale Optimization and Learning. While the first course (EE381V-11a) focused on convex optimization, with an emphasis on methods for large-scale problems, this course will focus on drawing inference from data - machine learning techniques, with a focus on methods for problems of large size and high dimensionality. Intended audience: This class is structured to be interesting and relevant to students who are using or plan to use machine learning in their research, and are interested in solving large-scale problems. The target audience is quite broad: graduate students from ECE, CS, OR, Math, DSSC, and related disciplines.