African Data Science Academy
The African Data Science Academy's mission is to facilitate human capacity building in data science and computational thinking at the University, nationally in South Africa, across Africa and globally. It develops and presents open courses offered by the School as well as bespoke courses developed for our industry and academic partners. We invite you to explore partnering with the African Data Science Academy for your training needs.
The following courses will be offered in 2022.
Full Course Information
| Presenter(s)||Department of Philosophy, Stellenbosch University|
- Dr Tanya de Villiers-Botha (CAE)
- Prof. Louise du Toit (CAE)
- Dr Schalk Engelbecht (KPMG, CAE)
- Dr Susan Hall (CAE)
- Prof. Johan Hattingh (CAE)
- Dr Andrea Palk (CAE)
- Prof. Vasti Roodt (CAE)
- Prof. JP Smit (CAE)
- Prof Johan Steyn (AI for Business)
- Prof. Anton van Niekerk (CAE)
- Prof. Minka Woermann (CAE)
| Duration||26 - 30 October 2021|
| Format||The course consists of online videos and synchronous lectures/workshops.|
| Target audience||Industry, students and other stakeholders in data science who need to
broaden their knowledge of data and AI ethics.|
| Certificate||Attendance Certificate.|
| Focus disciplines||This course is relevant across all data science areas.|
- It has become clear that the practicing of data science cannot be divorced from the ethical considerations. This short course provides an introduction to the ethics of data science. Participants will be given an overview of foundational ethical theory, which will then be applied to practical ethical concerns that arise in the context of data science, with the help of topical case studies. There will be specific focus on the South African and African contexts.
Participants will gain competency in the following:
• Familiarity with introductory ethical theory
• Familiarity with introductory data ethics
• Familiarity with introductory AI ethics
• Familiarity with prominent ethical concerns relating to data practices, for example, ownership of data, the governance of data practices and the like.
• Familiarity with prominent ethical concerns relating to the development, implementation, and use of AI technologies, such as algorithmic bias, responsibility in artificial decision making, AI for good, governance, and best practice.
• The ability to apply ethical theory to practical ethical problems that stem from data-related and AI-related practices.
Your Presenter, Dr Tanya de Villiers-Botha
Dr Tanya de Villiers-Botha will be presenting this course, together with her colleagues from the Department of Philosophy at Stellenbosch University. More information on the Department's world class academics can be found on their Department of Philosophy
| Presenter(s)||Mr Hans-Peter Baker and Prof Sugnet Lubbe|
| Duration||October 3 - December 8|
| Format||The course consists of online and synchronous lectures/tutorials.|
| Requirements||General computer literacy as well as some prior knowledge of first year mathematics and statistics taught at a university.|
| Target audience||Industry, students and other stakeholders interested in data science applied to finance/investments.|
| Certificate||Attendance Certificate.|
| Focus disciplines||This course is relevant for those interested in strengthening their research capacity in terms of basic statistical understanding and its application using R.|
- This course, presented over nine weeks, offers an introduction into the application of the programming language R to statistical analysis. R is statistical software particularly powerful in data analysis and graphical representation.
Your Presenter - Mr Hans-Peter Bakker and Prof Sugnet Lubbe
Mr Hans-Peter Bakker will be the principal presenter of this course. He is currently a full-time lecturer in the Department of Statistics and Actuarial Science at Stellenbosch University. He will be supported by Professor Sugnet Lubbe, also at Stellenbosch University's Department of Statistics and Actuarial Science.
| Presenter(s)||Prof Jacomine Grobler, Dr Sydney Kasongo, Dr Thorsten Schmidt-Durant|
| Duration||31 October - 4 November|
|Cost||R7,000.00 for attendance option, R8,500 for competence certificate|
| Format||Pre-recorded lectures and daily live sessions|
| Requirements||Bachelor's Degree|
| Target audience|
Graduates working in Industry, staff members and those considering postgraduate studies in Data Science
| Certificate||Attendance or Competence Certificate.|
| Focus disciplines||Industry (graduates) who have encountered or been exposed to data science, without having proper knowledge of the field or the process of facilitating a data science project|
The short course is designed as an introductory overview to data science explained at the hand of the data science project life cycle. A participant to this
course will gain knowledge in the following aspects:
- The data science project life cycle and the different role players involved,
- The aspects included in each of the data science project life cycle phases,
- The technologies applicable to the data science project life cycle,
- The di erent data formats and the requirements imposed by these formats on data science technologies,
- The process of constructing a data pipeline from raw data to knowledge, and
- The ethical challenges faced in data science, as well as data regulation and information privacy.
Your Presenter - Prof Jacomine Grobler, Dr Sydney Kasonga and Dr Thorsten Schmidt-Durant
Prof Jacomine Grobler is an associate professor in the Department of Industrial Engineering at Stellenbosch University. Dr Sydney Kasonga is a lecturer and Dr Thorsten Schmidt-Durant is a postdoctoral fellow in the same department. All three teach on the postgraduate data science programmes on offer by the Department.