Use statistical learning to solve real-world business problems.
8 weeks, excluding
orientation
7–10 hours per week,
entirely online
Weekly modules,
flexible learning
1
The ability to apply data science and analysis solutions to business situations, and analyse raw data and present it effectively in a visualisation.
2
The tools to build and modify robust models, using techniques such as regularisation, to help you solve business problems.
3
A practical grounding in Jupyter Notebook, one of the most widely used notebooks in data science.
4
A certificate of completion from the University of Cape Town (UCT), Africa’s leading university,1 as validation of your new data science and analysis skill set.
1 QS Top Universities (Aug, 2021).
Over the duration of this online short course, you’ll work your way through the following modules:
MODULE 1 Data Science and Statistical Learning
Gain an understanding of data science skills and the principles of statistical learning.
MODULE 2 Tree-Based Methods
Learn about mechanically partitioning the feature space to create a tree-based model.
MODULE 3 Managing the Complexity of Tree-Based Methods
Learn how to find more parsimonious models using pruning.
MODULE 4 Neural Networks
Gain an understanding of neural networks as a non-linear method for analysis of complex patterns.
MODULE 5 Managing the Complexity of Neural Networks
Learn how to apply the brakes on complexity in overparameterised neural networks.
MODULE 6 K-Means Clustering
Explore methods to find naturally occuring partitions in the feature space based on the geometric structure of the observed data.
MODULE 7 Hierarchical Clustering
Explore the mechanics and applications of hierarchical clustering.
MODULE 8 Data Science in the Real World
Use a culmination of skills to solve a problem using statistical learning on a real-world data set.
Please note that module titles and their contents are subject to change during course development.
Assess your knowledge of Python in preparation for this course with our readiness test. The test will gauge your competencies in mathematics and statistics, as well as your understanding of relevant programming languages.
Etienne Pienaar
Lecturer, Department of Statistical Sciences at the University of Cape Town
Pienaar is a postdoctoral fellow at UCT where he convenes the postgraduate diploma in entrepreneurship. He obtained a BSc in financial mathematics at the University of Johannesburg and subsequently completed a postgraduate diploma in actuarial science, and an honours in statistics at UCT. He then obtained a master’s, as well as a PhD, in statistics. Although his research focuses primarily on the analysis of non-linear jump diffusion processes and the development of computationally scientific techniques (and accompanying software packages), he has strong interests in machine learning and risk valuation for financial instruments.
Jean-Paul Van Belle
Professor of Information Systems and Director of the Centre for Information Technology and National Development in Africa at the University of Cape Town
Van Belle has written over 120 published peer-reviewed articles in the fields of service-oriented architecture, unified communications within businesses, open source software, mobile computing, and information and communication technologies for development. In 2012, he established the UCT-Samsung Mobile Innovation Lab at UCT.
“This course was the perfect introduction to the basics of data science and the various machine learning models in Python. I feel fully equipped to build on the strong foundations this course has given me.”
This UCT online short course is delivered in collaboration with online education provider GetSmarter, part of edX. Join a growing community of global professionals, and benefit from the opportunity to:
Gain verifiable and relevant competencies and earn invaluable recognition from an international selection of universities and institutions, entirely online and in your own time.
Enjoy a personalised, people-mediated online learning experience created to make you feel supported at every step.
Experience a flexible but structured approach to online education as you plan your learning around your life to meet weekly milestones.