Departments' graduate courses
Course start and periodicity may vary. Please see details for each course for up-to-date information. The courses are managed and administered by the respective departments. For more information about the courses, how to sign up, and other practical issues, please contact the examiner or course contact to be found in the course information.
- Course code: FSSY020
- Course higher education credits: 7.5
- Department: ELECTRICAL ENGINEERING
- Graduate school: Signals and Systems
- Course is normally given: Every 2nd year, next time it will be given in SP4, spring, 2023.
- Language: The course will be given in English
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. Additional information
The course is also part of the master program in information and communication technologies (MPICT). Additional information is available in the student portalApplication code:
Contact Giuseppe Durisi
Telephone: 031 772 18 21