EAI732 Intelligent Systems

Semester: First (only)

Research Group: Intelligent Systems

NOTE:   Before registering for ANY postgraduate studies as part of the ISG, students MUST discuss potential research topics with one of the ISG study leaders and/or the group leader. The EAI732 module is only available to approved students and registrations after the start of the semester are not allowed.


The EAI732 module is part of the fixed Honours curriculum of the ISG. The goal of this module is to provide postgraduate engineering students with background related to intelligent systems. The official scope of the module is defined as:

This module provides the theoretical background necessary to understand, research and develop real-world software and hardware systems that incorporate and exhibit intelligent behaviour. The module incorporates advanced theory from fields such as Artificial Intelligence, Computational Intelligence, Machine Learning, Pattern Recognition and Signal Processing. Core topics of the module include: Bayesian Theory, Neural Networks, Kernel Methods, Graphic Models, and Numerical Bayesian Methods.


Whilst there are no official prerequisites for EAI732, there are a number of implied prerequisites. Please see the study guide for more details. See also the complementary module EAI733 Advanced Topics in Intelligent Systems.

Note that registration for the EAI732 module is subject to approval and the module is generally only available to students of the UP Department of Electrical, Electronic and Computer Engineering, or students with an ISG staff member as postgraduate supervisor or co-supervisor. 

Contact information

  Name Office  Email Address
Lecturer Dr A de Freitas Eng 1, 15-18 allan . defreitas @ up . ac . za
Lecturer Prof Pieter de Villiers Eng 3, 7-54 pieter . devilliers @ up . ac . za
Lecturer Mr H Grobler Eng 1, 13-17 hans . grobler @ up . ac . za
Lecturer Prof Pieter Jacobs Eng 1, 13-15 jpjacobs @ up . ac . za
Lecturer Prof Herman Myburgh Eng 1, 15-5 herman . myburgh @ up . ac . za

The preferred contact medium is email.

Prescribed Text

Pattern Recognition and Machine Learning
by Christopher M. Bishop

Hardcover: 738 pages

Publisher: Springer

ISBN: 978-0387310732

Book Home Page: http://research.microsoft.com/en-us/um/people/cmbishop/prml/

It is strongly recommended that students obtain the textbook as soon as possible and begin working through the first few chapters. 

Study Guide

The module content is divided into a number of themes corresponding to the contents of the prescribed text. The themes and the study schedule are given in the study guide. Details of the study materials and assignments are only made available to students registered for the module. It is therefore crucial that students who wish to take the module ensure that their registration is completed as soon as possible (before the start of the semester).

Published by Hans Grobler

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