Data Science

Undergraduate

BDatSci

Focal area: Statistical Learning

In almost all environments, decision-making is driven by massive amounts of data, which means that there is a dire need for skilled individuals who can make sense of this data deluge. In general, data science entails the gathering and storage of data, the transformation and graphical representation of data and the analysis of data in order to make predictions or inferences. The statistical learning focal area entails identifying trends and patterns in data, and using these to construct statistical models, which can be used to predict or classify. This is an important task across all industries, meaning that individuals with these particular skills can work on solving real-world problems found in a variety of domains. 

Admission Requirements

  • Overall National Senior Certificate average of at least 70%, excluding Life Orientation
  • Mathematics 80%
  • One of the following:
    • Afrikaans Home Language 60% or
    • English Home Language 60% or
    • Afrikaans First Additional Language 75% or
    • English First Additional Language 75%

Programme Content

First Year | 120 credits

​Compulsory Modules
Computer Science113 | 16 credits​ OR
114 | 16 credits​
144 | 16 credits​
Data Science141 | 16 credits​
​Mathematics114 | 16 credits​
144 | 16 credits​
Probability Theory and Statistics114 | 16 credits​
Plus
Actuarial Science112 | 8 credits​
Applied Mathematics144 | 16 credits​
Or
Economics114 | 12 credits​
144 | 12 credits​

Second Year | 128 credits

​Compulsory Modules
Computer Science214 | 16 credits​
244 | 16 credits​
Data Science241 | 16 credits​
​Mathematical Statistics214 | 16 credits​
245 | 8 credits​
246 | 8 credits​
​Mathematics214 | 16 credits​
244 | 16 credits​
Operations Research214 | 16 credits

Third Year | 128 credits

​Compulsory Modules
Computer Science315 | 16 credits​
343 | 16 credits​
Data Science316 | 16 credits​
346 | 16 credits​
​Mathematical Statistics312 | 16 credits​
316 | 16 credits​
344 | 16 credits​
364 | 16 credits​

Fourth Year | 124 credits

​Compulsory Modules
Data Science research in Statistical Learning471 | 40 credits​
Introduction to Statistical Learning441 | 12 credits​
Machine Learning441 | 16 credits​
Electives (min 56 credits)
Bayesian Statistics441 | 16 credits
Multivariate Statistical Analysis A441 | 16 credits
Multivariate Statistical Analysis B441 | 16 credits
Stochastic Simulation441 | 12 credits
Time Series Analysis441 | 12 credits

BCom | Mathematical Sciences

Focal area: Data Science

Data Science is an interdisciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from data in various forms, both structured and unstructured. Artificial intelligence, machine learning, big data – these concepts are at the core of data science. With the deluge of data, comes the increasing need for people to make sense of the data. Studies have shown that statistical analysis and data acumen are some of the top skills in demand globally at the moment, and that demand far outstrips supply.

Programme structure

The BCom (Mathematical Sciences) programme offers you a relatively free choice of modules. In choosing your modules, please take note of the stipulations regarding timetable clashes in the general section at the beginning of this chapter. It is also possible within this programme to focus on a specific area of study, called a focal area.

Focal areas

The objective of focal areas is to help you choose a specific career focus within the BCom (Mathematical Sciences) programme. The focal area is not a programme, and the module combination is only a recommendation for you to make more focussed module choices. The module choices in the tables describing each focal area fit in with the lecture and assessment timetables, but you are still free to take other module combinations in the broader programme if lecture and assessment timetables allow it.

There are three focal areas within the BCom (Mathematical Sciences) programme. These are:

  • Data Science
  • Financial Risk Management
  • Operations Research

Admission Requirements

  • Overall National Senior Certificate average of at least 70%, excluding Life Orientation
  • Mathematics 75%
  • One of the following:
    • Afrikaans Home Language 50% or
    • English Home Language 50% or
    • Afrikaans First Additional Language 60% or
    • English First Additional Language 60%

Programme content

First Year | 140 credits

​Compulsory Modules
​Actuarial Science112 | 8 credits​
​Probability Theory and Statistics144 | 16 credits​
​Mathematics114 | 16 credits​
144 | 16 credits​
Data Science141 | 16 credits​
Computer Science114 | 16 credits​
144 | 16 credits​
Economics114 | 12 credits
Financial Accounting188 | 24 credits

Second Year | 120 credits

​Compulsory Modules
​Mathematical Statistics214 | 16 credits​
245 | 8 credits​
246 | 8 credits​
​Mathematics214 | 16 credits​
244 | 16 credits​
Data Science241 | 16 credits​
Economics144 | 12 credits​
​Computer Science214 | 16 credits​
Business Management113 | 12 credits

Third Year | 134 credits

​Compulsory Modules
Business Management142 | 6 credits
Data Science316 | 16 credits​
346 | 16 credits
​Mathematical Statistics312 | 16 credits​
316 | 16 credits​
344 | 16 credits​
364 | 16 credits​
Computer Science315 | 16 credits​
343 | 16 credits