Information theory

Aim

This course offers an introduction to information theory and its application to digital communication, statistics, and machine learning.

One important feature of the information-theory approach is its ability to provide fundamental results, i.e., results that demonstrate the optimality of certain procedures.

Obtaining results of this flavor is useful for many reasons: for example, we can assess whether achieving a target error probability in the transmission of information is feasible; we can determine how many data samples need to be collected to distinguish between two or more statistical hypotheses, or how many examples are needed to train a machine learning algorithm.

Equivalent to the Master's course SSY210. See the Study Portal for course details and TimeEdit for the schedule.