Coding Summer School: Data Science and Machine Learning

Department of Mathematics, Science and Technology Education

Humanities Mathematics, Science and Technology Education Teaching and Learning

The Central University of Technology, Free State (CUT) is proud to participate in the 17th CHPC & 9th NITheCS Coding Summer School, a nationally recognised intensive training programme in Data Science and Machine Learning. This two-week summer school offers students, researchers, and industry professionals access to high-quality, structured training that would typically cost between R20 000 and R80 000 through commercial providers, at no cost to successful applicants.

What you will learn

The programme is divided into two comprehensive tracks, delivered by leading experts in computational and data sciences:

Data Science Track:

  • Workflow management and ETL (Extract, Transform, Load)
  • Exploratory Data Analysis (EDA) and Visualisation
  • Terminal Skills and Leveraging AI Tools

Machine Learning Track:

  • Computational Thinking
  • Probability Theory and Statistics
  • Machine Learning and AI Fundamentals

Who should attend

This summer school is designed for:

  • Final-year undergraduate students planning postgraduate study
  • Postgraduate students (Honours, Master's, Doctoral)
  • Researchers and industry professionals seeking to strengthen data science capabilities

Relevance across disciplines

Data science and machine learning skills are increasingly essential across all fields of study and professional practice:

  • Education: Student success prediction, learning analytics, curriculum evaluation, and assessment data analysis
  • Humanities and Social Sciences: Survey analysis, policy research, digital humanities, text and document analysis, and community impact studies
  • Management Sciences: Business analytics, forecasting, operational efficiency, and decision support
  • Health and Environmental Sciences: Public health data analysis, epidemiological studies, environmental monitoring, and sustainability research
  • Engineering, Physics and ICT: Experimental data analysis, modelling and simulation, sensor data processing, optimisation, and AI applications

Prerequisites:

  • Background in Python programming (essential)
  • Must pass the entrance test (emailed after registration)
  • Must be registered at a South African university

New to Python? Prepare by completing the free Python for Beginners course on Alison or attending a free NITheCS Software Carpentry Workshop (visit nithecs.ac.za for details).

Important notes and how to apply

  • Space is limited at each venue.
  • Travel and accommodation are not covered.
  • Applications must be submitted by 15 December 2026 at 12:00.

For more information contact, Dr ZW Dlamini, zdlamini@cut.ac.za

For more information about the programme→ Applications are submitted through the CHPC support portal→