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School of Computing · ANU College of Systems and Society
Information theory studies the fundamental limits of the representation and transmission of information. This course provides an introduction to information theory, studying fundamental concepts such as probability, information, and entropy and examining their applications in the areas of data compression, coding, communications, pattern recognition and probabilistic inference.
Assignment 1
Learning outcomes 1, 7
Assignment(s)
Learning outcomes 1, 2, 3, 4, 5, 6, 7
Final Exam
Learning outcomes 1, 2, 3, 4, 5, 6, 7
Lectures and tutorial sessions plus self study for a total of 130 hours.
David MacKay, ``Information Theory, Inference, and Learning Algorithms'', Cambridge University press, (primary text; available free http://www.inference.org.uk/mackay/itila ) Preliminary Reading "Elements of Information Theory" by Cover and Thomas, 2nd Edition, New York, Wiley, 2006. "Pattern Recognition and Machine Learning," by Christopher M. Bishop