Course Description 

This course introduces students to fast and scalable optimization algorithms that play important roles in data science. Students will not only learn about implementation of the algorithms but also understand why they are correct and fast (theoretical guarantees). Both mathematical analysis skills and programming skills of the student will be trained. 

Prerequisites 

Real Analysis, Linear Algebra, Operational Research, Statics and Probability, Optimization (Linear and Convex). In general, the course will be very much self-contained.