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Computer Science and Applied Maths
Big Data Analytics The BSc Honours in Big Data Analytics is designed to blend multi-disciplinary subjects and provide students with the research and professional skills to design smart technologies. This is a 1 year full-time degree.
Big Data Analytics The BSc Honours in Big Data Analytics is designed to blend multi-disciplinary subjects and provide students with the research and professional skills to design smart technologies. This is a 1 year full-time degree.

Qualification: BScHons

Faculty: Science

Duration: 1 year

School: Computer Science and Applied Mathematics

Study mode: Full-time


“Big Data” captures the idea of managing vast amounts of data using a variety of modern computing technologies and infrastructure from a variety of different sources. To manage, develop and understand the required technologies, people trained in the intersection of subjects ranging from statistics, information and computer science, system design and social sciences are needed. There are individuals who are able to leverage emerging technologies and interact with interdisciplinary teams of specialists.

The “BSc Honours in Big Data Analytics” programme is designed by the School of Computer Science and Applied Mathematics at Wits to blend multi-disciplinary subjects together and to provide students with the research and professional skills to master and design smart technologies.

The course will introduce postgraduate computer science students to the field of big data analytics. The course has a focus on strong computational and mathematical foundations embedded in practical application. Students having completed the course would have been exposed to all facets of the big data analytics pipeline from technology deployment, through machine learning, to optimisation and multivariate statistics. 

As part of the programme, students are required to complete an applied research project with a focus on a real world/industry big data analytics problem. Students are encouraged to find mentorship within industry and additional cohort supervision is provided by subject matter experts from within the school.

The research project takes the student through all aspects of research design methodology from proposal through literature review to implementation and analysis of results. The skills acquired in learning how to do research – critical thinking, written and oral presentation skills, collation, and analysis of large amounts of new information, and the actual conducting of research – are invaluable in industry as well as for further academic pursuit.


As students will be required to program, you should be proficient in at least one procedural or object oriented programming language. Being able to use R or Matlab may be beneficial, but unless you have used the control flow constructs of these languages this will not be sufficient.

The BSc(honours) in Big Data Analytics is offered full-time only. It does not include an internship. However, the programmes includes a research project that should have real world application and will be guided by a supervisor

There is currently no bridging programme available.

If any bursaries become available for this programme, they will be advertised on the school website.

The programme comprises eight lectured topics, five of which are compulsory and three of which are elective. The five compulsory courses are specifically chosen to give students a broad introduction to big data analytics with the electives being subjects the students can use to specialise their skills. The final component is a compulsory Research Project in Big Data Analytics.

Compulsory Courses:
  • Research Project: Big Data Analytics
  • Introduction to Research Methods
  • Adaptive Computation and Machine Learning
  • Data Analysis and Exploration
  • Introduction to Data Visualisation and Exploration
  • Discrete Optimisation
Elective Courses:
  • Applications of Algorithms
  • Computer Vision
  • Distributed Computing
  • High-Performance Computing and Scientific Data Management
  • Special Topics in Computer Science
  • Mathematical Foundations of Data Science
  • Databases


An undergraduate BSc degree with a major in computer science or equivalent (NQF 7) is required and at least a second year in a mathematics equivalent. However, if you have a BSc degree and can show that your degree had a large computer science like component (data structures, databases, programming languages, algorithms) or that you have done additional course work such as a diploma in programming these will be considered.

Admission into the Big Data Analytics Honours programme is highly selective. Students must have at least 2nd Year Mathematics and or Computer Science. To be accepted, students must have performed well in their undergraduate degrees (we use a guideline of 70% in third-year level courses, though this is by no means a guarantee of acceptance into the programme).

Proficiency in at least one procedural or object oriented programming language.

30 November 2021

  • Applications are handled centrally by the Student Enrolment Centre (SEnC). Once your application is complete in terms of requested documentation, your application will be referred to the relevant School for assessment. Click here to see an overview of the Wits applications process.
  • Please apply online. Upload your supporting documents at the time of application, or via the Self Service Portal.
  • Applicants can monitor the progress of their applications via the Self Service Portal.
  • Selections for programmes that have a limited intake but attract a large number of applications may only finalise the application at the end of the application cycle.

Please note that the Entry Requirements are a guide. Meeting these requirements does not guarantee a place. Final selection is made subject to the availability of places, academic results and other entry requirements where applicable.

International students, please check this section.

For more information, contact the Student Call Centre +27 (0)11 717 1888, or log a query at

Click here to see the current average tuition fees. The Fees site also provides information about the payment of fees and closing dates for fees payments. Once you have applied you will be able to access the fees estimator on the student self-service portal.

For information about postgraduate funding opportunities, including the postgraduate merit award, click here. Please also check your School website for bursary opportunities. NRF bursaries: The National Research Foundation (NRF) offers a wide range of opportunities in terms of bursaries and fellowships to students pursuing postgraduate studies. External bursaries portal: The Bursaries South Africa website provides a comprehensive list of bursaries in South Africa.