Information and Coding Theory - Winter 2021

TTIC 31200/CMSC 37220

T Th 1:00-2:20 (Zoom)

Discussion: F 2-3 pm (Gather)

Office hours: W 1-2 pm (Gather)

Instructor: Madhur Tulsiani

TA: Goutham Rajendran


This course is meant to serve as an introduction to some basic concepts in information theory and error-correcting codes, and some of their applications in computer science and statistics. We plan to cover the following topics:

  • Introduction to entropy and source coding. Some applications of entropy to counting problems.
  • Mutual information and KL-divergence. Method of types and hypothesis testing. Minimax rate bounds.
  • I-projections, maximum entropy, exponential families and applications.
  • Introduction to error-correcting codes. Unique and list decoding of Reed-Solomon and Reed-Muller codes.
  • Applications of information theory to problems in theoretical computer science.

The course will have 4-5 homeworks (60 percent) and a final (40 percent).

There is no textbook for this course. A useful reference is ``Elements of Information Theory'' by T. M. Cover and J. A. Thomas. Also take a look at the resources section below.

Access information for lectures, discussions and office hours, is available via the Canvas page for the course.

Homeworks and Announcements

Lecture Plan and Notes