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PURPOSE OF THE PROGRAM

The Department of Applied Information System, in collaboration with the Institute for Intelligent System is pleased to offer the
short learning programme on Computational Intelligence for Industry. The University of Johannesburg is playing a leading
role in driving the upskilling and reskilling of professionals as we enter the Fourth Industrial Revolution. A critical aspect of the Fourth Industrial Revolution is Artificial Intelligence, as it begins to drastically change the nature of our work environments and jobs. The purpose of this short learning program is to provide professionals, from any area, with a working knowledge of key Artificial Intelligence and Machine Learning tools.

Upon completion of this short learning program, participants will be able to perform data analytics and construct predictive
models in their field of practice.

ENTRY REQUIREMENT

This short learning programme is at a South African National Qualification Framework (NQF) Level 8. Applicants require at least an NQF level 7 qualification, that includes basic mathematics (NQF level 5), or equivalent.

TIMELINES

Computational Intelligence for Industry is a one semester programme that begins in July 2019 and ends November 2019. Classes will be held twice a month from 3pm to 7pm. The programme consists of a total of 12 classes. The closing dates for applications for the July – November 2019 intake is 28 June 2019.


HOW TO APPLY

Visit the Study@UJ site  to apply for this program. All applications are done online.

REGISTRATION AND FEES

Fees – R 12 000
Ms Lerato Mofokeng: leratom@uj.ac.za
Dr Roelien Brink: rbrink@uj.ac.za

PROGRAMME OVERVIEW

This programme is offered through a mix of lectures and practical (hands-on) sessions. Supporting study materials will be provided.

The following topics will be covered:

  • Introduction to Python
  • Introduction to machine learning
  • Basic Statistics and Probability Theory
  • Naïve Bayes Classifier
  • Bayesian Networks
  • Sensitivity Analysis
  • Decision Trees
  • Support Vector Machines (SVM)
  • Instance based learning
    • K-Nearest Neighbor
    • K-Means Clustering
  • Artificial Neural Networks
  • Post-processing
Required mathematical and statistical foundation will also be provided to the participants at the start of the program.

ASSESSMENT

Assessments in this programme comprise written tests, assignments, practical work and a written exam. Upon successful
completion of the programme, participants will receive a certificate.

ENQUIRIES

For further information and queries relating to this programme, you may contact:
Dr Barnabas Gatsheni (PhD Edinburgh) bgatsheni@uj.ac.za; 011 559 1506
Dr Wesley Doorsamy (PhD Wits) wdoorsamy@uj.ac.za; 011 559 6904
Prof B S Paul (PhD IIT) bspaul@uj.ac.za; 011 559 4404