Course overview
- Course codeFSSY020
- ECTS credits7.5
- DepartmentELECTRICAL ENGINEERING
- Graduate schoolElectrical Engineering
- PeriodicityGiven every odd year year in SP4
- LanguageEnglish
- ApplicationContact the course coordinator
Course coordinator
- Giuseppe Durisi
- Full Professor, Communication, Antennas and Optical Networks, Electrical Engineering
About the course
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.