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52359-01 - Lecture: Information Theory 4 CP

Semester fall semester 2018
Course frequency Irregular
Lecturers Volker Roth (, Assessor)
Content - probabilities, random variables
- measuring uncertainty: entropy, relative entropy and mutual information
- data compression
- channel coding
- communication over channels
Learning objectives After completion of this course you should understand
- why and how to measure the amount of uncertainty
- the meaning of probabilities, entropies, mutual informations etc.
- the principles of coding, compression, communication and information retrieval.
Bibliography David J.C. MacKay: Information Theory, Inference, and Learning Algorithms
Thomas M. Cover and Joy A. Thomas: Elements of Information Theory


Admission requirements Introductory courses in mathematics and statistics
Language of instruction English
Use of digital media No specific media used
Course auditors welcome


Interval weekly
Date 18.09.2018 – 09.01.2019

No dates available. Please contact the lecturer.

Modules Modul: Applications and Related Topics (Bachelor's degree subject Computer Science)
Modul: Wahlbereich Informatik (Bachelor's degree subject Computer Science (Start of studies before 01.08.2016))
Module Specialisation: Computational Intelligence (Bachelor's Studies: Computer Science (Start of studies before 01.08.2016))
Module: Applications and Related Topics (Bachelor's Studies: Computer Science)
Assessment format continuous assessment
Assessment registration/deregistration Reg.: course registration, dereg: cancel course registration
Repeat examination no repeat examination
Scale 1-6 0,5
Repeated registration as often as necessary
Responsible faculty Faculty of Science,
Offered by Fachbereich Informatik