COMPUTER SCIENCE 711 - COS 711

FacultyNatural Sciences
Home DepartmentComputer Science
Module TopicArtificial Intelligence
Generic Module NameComputer Science 711
Alpha-numeric CodeCOS711
NQF Level  8
NQF Credit Value15
DurationSemester
Proposed semester to be offered.First
Programmes in which the module will be offeredBSc Hons (Computer Science) (3735)
Year level1
Main Outcomes

On completion of this module, students should be able to:

  • Understand key concepts and theories in machine learning.
  • Develop and implement key machine learning algorithms including decision tree learning, Bayesian           learning, back-propagation neural networks, and genetic algorithms.
Main Content
  • Concept Learning,
  • Decision Tree Learning,
  • Artificial Neural Networks,
  • Bayesian Learning,
  • Instance-Based Learning,
  • Evolutionary Computation,
  • Computational Learning Theory
Pre-requisite modulesNone
Co-requisite modulesNone
Prohibited module CombinationNone
Breakdown of Learning TimeHoursTimetable Requirement per weekOther teaching modes that does not require time-table
Contact with lecturer: / tutor:28Lectures p.w.3 
Assignments & tasks:28Practicals p.w.2
Practicals:28Tutorials p.w.0
Tutorials:0  
Tests & Examinations:8  
Selfstudy:58  
Other:0  
Total Learning Time150  
Methods of Student Assessment

Continuous Assessment (CA): 100%

Final Assessment (FA): 0%

Assessment Module typeContinuous Assessment (CA)