Bachelor of Science (Statistics & Computer Science)
Overview
This three-year undergraduate program results in the degree of Bachelor of Science (BSc), which encompasses majors within the disciplines of Computer Science and Statistics, as well as Mathematics modules up to second year.
This strong quantitative and computational foundation equips graduates with the core skills required for a career in data science, including programming, statistical modelling, data analysis and problem-solving.
SAQA
84728
NQF LEVEL
07
DURATION
3 Years
CAO CODE
KN-W-BG4 (Westville Campus)
KN-P-BG4 (PMB Campus)
CLOSING DATE
30 September
Entry Requirements
NSC degree pass with Maths Level 4, English and Life Orientation Level 4 and either Agricultural Science or Life Sciences or Physical Science Level 4. In addition, an Application Performance Score (APS) of at least 30 is required.
Learn how to calculate your APS here.
How to apply?
All first-time South African applicants to UKZN for entry into degree/ diploma study (Grade 12s and undergraduate transfer students from other institutions) must apply via the Central Applications Office (CAO).
Students applying to study in this program should apply for a BSc (General). Students can choose to do this either at the Westville or Pietermaritzburg campuses.
Note that this is a general degree and that the selection of the specific modules according to the Statistics and Computer Science majors will only take place during registration in January/February of the academic year.
Modules
The advantage of UKZN’s undergraduate BSc general program is that it is versatile. The BSc starts off general in first year with 6 core modules and 2 electives.
Students therefore have the option of taking two modules from a range of electives such as chemistry, physics, and economics. This allows them to re-assess their interests and strengths in second year, where they have the option of changing their majors from Statistics or Computer Science if they do not enjoy these modules.
Semester 1
- Introduction to
Computer Science – COMP100 (16 Credits) - Introduction to Calculus – MATH130 (16 Credits)
- Introduction to Statistics – STAT130 (16 Credits)
- Elective (16 Credits)
Total Credits: 64 Credits
Semester 2
- Computer Programming – COMP102 (16 Credits)
- Calculus and Linear Algebra – MATH140 (16 Credits)
- Statistical Methods – STAT140 (16 Credits)
- Elective (16 Credits)
Total Credits: 64 Credits
Semester 1
- Object- Oriented Programming – COMP200 (16 Credits)
- Probability Distributions STAT230 (16 Credits)
- Advanced Calculus and Linear Algebra – MATH212 (16 Credits)
- Discrete Mathematics with Applications MATH236 (16 Credits)
Total Credits: 64 Credits
Semester 2
- Data Structures – COMP201 (16 Credits)
- Statistical Inference – STAT240 (16 Credits)
- Further Calculus and Introductory Analysis MATH251 (16 Credits)
- Elective (16 Credits)
Total Credits: 64 Credits.
Semester 1
- Advanced Programming – COMP315 (16 Credits)
- Computer Systems – COMP313 (16 Credits)
- Linear Models – STAT301 (16 Credits)
- Applied Probability Models – STAT395 (16 Credits)
Total Credits: 64 Credits
Semester 2
- Theory of Computation – COMP314 (16 Credits)
- Artificial Intelligence – COMP304 (16 Credits)
- Biostatistics Methods – STAT305 (16 Credits)
- Radom Processes – STAT350 (16 Credits)
Total Credits: 64 Credits.
- Total Credits for Qualification: 384
What do they actually do?
Graduates from this degree are equipped with both the theoretical and computational expertise needed to extract value from data across Banking, Business, Government and Industry. They combine statistical reasoning, mathematical modelling and advanced programming skills to analyse complex datasets, build predictive models, and develop intelligent systems that support strategic decision-making.
They play a critical role in transforming raw data into actionable insights, helping organisations identify trends, optimise processes, manage risk, and stay competitive in data-driven environments.
Typical responsibilities of the job include:
- Designing and managing data acquisition processes
- Developing algorithms and computational models
- Analysing structured and unstructured data
- Building predictive and machine learning models
- Applying statistical and mathematical techniques to complex real-world problems
- Designing and implementing data management systems and software solutionsVisualising and communicating insights to stakeholders
- Acting in a technical or strategic consultancy capacity
Areas of Employment
This multidisciplinary skill set prepares graduates for careers in data science, artificial intelligence, quantitative analytics, software development, financial modelling, and research. Here are some examples of employers and types of companies in South Africa and abroad that hire these graduates:
- Financial Services & Banking (FNB, Standard Bank, ABSA, Sanlam)
- Technology & Digital Companies (Takealot, Media24, Microsoft)
- Retail, FMCG & Consumer Analytics (Mr Price, Woolworths, Spar, Checkers)
- Telecommunications (MTN, Vodacom)
- Insurance Companies (Discovery)
Types of Roles
Graduates with this multidisciplinary degree could be employed in roles such as:
- Data Scientist/Data Analyst
- Machine Learning Engineer/AI Specialist
- Business Intelligence Analyst
- Quantitative Analyst
- Software Developer or Data Engineer
- Analytics Consultant
Apply today and take the next step toward your future.
