Interdisciplinary Programme: Bachelor of Data Science

   About the programme

Do you have a passion for computers, math, and discovering answers through data analysis? The Bachelor of Data Science (BDatSci) programme will give you a thorough grounding in all aspects of the data lifecycle, including data collection, processing, analysis, and visualisation. Also, to better prepare you for industry, you choose one of eight focus areas (or streams). This ensures that you either develop expertise for applying data science in a specific area, or specialise in a certain aspect of data science. Artificial intelligence, machine learning, statistical learning, deep learning, big data - these are all concepts at the core of the discipline called Data Science.

Work across nearly all domains is becoming more data-driven. Graduates from this programme should be sought-after in a multitude of environments facing the challenges posed by the large quantities of data being generated and collected almost everywhere.

Download a brochure on the Bachelor of Data Science here and a poster here.

   Programme content

The BDatSci programme consists of a set of core compulsory modules on all year levels. The core modules lay the foundation for studies in the field of data science, while your choice of focal area (or stream) largely determines the other modules.

Four faculties collaborate to offer this four-year programme, namely AgriSciences, Arts and Social Sciences, Economic and Management Sciences, and Science. You will register for the BDatSci in the faculty that offers the focal area of your choice. The faculty where you are registered will award the degree.  See the various descriptions of the focal areas in the relevant faculty’s Calendar part given in brackets:

  • Analytics and Optimisation (Faculty of Economic and Management Sciences, page 62) teaches techniques that break real-world problems down into basic components and then solving them in defined steps to find optimal solutions.
  • Applied Mathematics (Faculty of Science, page 81) gives students more extensive training in mathematical modelllng techniques that are extremely useful for effective data analysis.
  • Behavioural Economics (Faculty of Economic and Management Sciences, page 63) investigates how psychological and economic factors affect decisions made by investors, consumers, workers, politicians, companies and managers.
  • Computer Science (Faculty of Science, page 80) gives students more extensive training in effective data organisation and processing, as well as in relevant artificial intelligence and machine learning techniques.
  • GeoInformatics (Faculty of Arts and Social Sciences, page 64) is the science and technology dealing with the structure and character of spatial information; its capture, classification and qualification; its storage, processing, portrayal and dissemination.
  • Statistical Genetics (Faculty of AgriSciences, page 48) uses statistical methods to make inferences of genetic data in fields such as population quantitative genetics (for example by plant breeders and conservation geneticists) and genetic epidemiology (which studies the effects of genes on diseases).
  • Statistical Learning (Faculty of Economic and Management Sciences, page 51) entails identifying trends and patterns in data, and using these to construct statistical models, which can predict or classify.
  • Statistical Physics (Faculty of Science, page 82) develops students’ expertise in Physics, preparing students for data analysis challenges in the domain of physics. 

However, if you are interested in following another career path but wish to equip yourself with strong Data Science expertise, consider one of the University’s other programmes with Data Science as a focal area. Besides the BDatSci dedicated to Data Science, the following programmes offer Data Science as a focal area:

   Admission requirements

  • An NSC aggregate of at least 80% (excluding Life Orientation)
  • Mathematics 80%

Plus 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%*

* The medium of instruction of the focal areas offered by the Faculty of Economic and Management Sciences is English. Candidates who wish to study in this faculty, therefore, have to meet the requirement of English Home Language or English First Additional Language.

   About the programme

Do you have a passion for computers, math, and discovering answers through data analysis? The Bachelor of Data Science (BDatSci) programme will give you a thorough grounding in all aspects of the data lifecycle, including data collection, processing, analysis, and visualisation. Also, to better prepare you for industry, you choose one of eight focus areas (or streams). This ensures that you either develop expertise for applying data science in a specific area, or specialise in a certain aspect of data science. Artificial intelligence, machine learning, statistical learning, deep learning, big data - these are all concepts at the core of the discipline called Data Science.

Work across nearly all domains is becoming more data-driven. Graduates from this programme should be sought-after in a multitude of environments facing the challenges posed by the large quantities of data being generated and collected almost everywhere.

Download a brochure on the Bachelor of Data Science here and a poster here.

   Programme content

The BDatSci programme consists of a set of core compulsory modules on all year levels. The core modules lay the foundation for studies in the field of data science, while your choice of focal area (or stream) largely determines the other modules.

Four faculties collaborate to offer this four-year programme, namely AgriSciences, Arts and Social Sciences, Economic and Management Sciences, and Science. You will register for the BDatSci in the faculty that offers the focal area of your choice. The faculty where you are registered will award the degree.  See the various descriptions of the focal areas in the relevant faculty’s Calendar part given in brackets:

  • Analytics and Optimisation (Faculty of Economic and Management Sciences, page 62) teaches techniques that break real-world problems down into basic components and then solving them in defined steps to find optimal solutions.
  • Applied Mathematics (Faculty of Science, page 81) gives students more extensive training in mathematical modelllng techniques that are extremely useful for effective data analysis.
  • Behavioural Economics (Faculty of Economic and Management Sciences, page 63) investigates how psychological and economic factors affect decisions made by investors, consumers, workers, politicians, companies and managers.
  • Computer Science (Faculty of Science, page 80) gives students more extensive training in effective data organisation and processing, as well as in relevant artificial intelligence and machine learning techniques.
  • GeoInformatics (Faculty of Arts and Social Sciences, page 64) is the science and technology dealing with the structure and character of spatial information; its capture, classification and qualification; its storage, processing, portrayal and dissemination.
  • Statistical Genetics (Faculty of AgriSciences, page 48) uses statistical methods to make inferences of genetic data in fields such as population quantitative genetics (for example by plant breeders and conservation geneticists) and genetic epidemiology (which studies the effects of genes on diseases).
  • Statistical Learning (Faculty of Economic and Management Sciences, page 51) entails identifying trends and patterns in data, and using these to construct statistical models, which can predict or classify.
  • Statistical Physics (Faculty of Science, page 82) develops students’ expertise in Physics, preparing students for data analysis challenges in the domain of physics. 

However, if you are interested in following another career path but wish to equip yourself with strong Data Science expertise, consider one of the University’s other programmes with Data Science as a focal area. Besides the BDatSci dedicated to Data Science, the following programmes offer Data Science as a focal area:

   Admission requirements

  • An NSC aggregate of at least 80% (excluding Life Orientation)
  • Mathematics 80%

Plus 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%*

* The medium of instruction of the focal areas offered by the Faculty of Economic and Management Sciences is English. Candidates who wish to study in this faculty, therefore, have to meet the requirement of English Home Language or English First Additional Language.