Class Information
This module provides the opportunity for students to apply the theoretical Big Data Science knowledge gained in the core part of this degree. The course involves a blend of lectures and practical group assignments.
Students are expected to identify and work with a collaborator who takes ownership of the project. This collaborator can be an industry partner or a researcher within one of the participating departments. Projects are based on the entire big data lifecycle, including data gathering, analysis, and a final technical report.
Course Structure
The course is organized into four blocks that follow the data science lifecycle:
- Scoping and EDA - Problem definition, project scoping, and exploratory data analysis
- Modelling - Analytical modelling (descriptive, exploratory, inferential, predictive, causal, mechanistic) and evaluation
- Visualisation and Deployment - Communicating insights and deploying solutions
- Putting It All Together - Final project integration, model cards, and exhibition
Outcomes
This module combines first-year modules of the MIT program into practice through a Data Science project. After successful completion of this module, students will be able to:
- Break down the entire data science life cycle of a project
- Work effectively with a project partner
- Deliver a complete Data Science solution
Instructors
The module has been taught by the following instructors since 2020:
- Prof. Vukosi Marivate: Vukosi has a background in Machine Learning and Artificial Intelligence and is interested in the role of Data Science in Society.
- Dr. Abiodun Modupe: Abiodun is interested in the confluence of artificial intelligence for natural language processing and speech recognition.