Instructor: Prof. Vivek Borkar

Session: 2019-2020

Prerequisites: N/A

Course content and structure:

1) Real analysis, hyperplanes, Convex sets and convex functions. 2) Linear programming. 3) Convex optimization techniques. 4) Some non-convex optimization techniques.

Feedback on lectures:

The instructor covers a lot of topics in a very small time span. It is easy to lose track of what is going on in the class but revising the notes before the next class and openly asking doubts improves the understanding. Asking doubts (even the lamest) is utmost important in this class else you may get blank very easily. The instructor regularly uploads supplementary notes for the content he covers.

Feedback on tutorials and exams:

Some of the exam questions were based on the questions mentioned in the supplementary notes. The others were easy and required a very basic understanding of the content. There were three exams of 1:30 hours each during the class timings. Weightage for each test was roughly equal.

Difficulty (on a scale of 1 being very easy to 5 being very hard): 5

Textbooks & References:

S. Boyd and L. Vandenberghe, Convex Optimization Dimitri P. Bertsekas, Nonlinear Programming Rangarajan K. Sundaram, A First Course in Optimization

Grading Statistics: Refer asc

Additional comments & what you learnt from the course: Its better to take the course in the 4th year.