Course Content
The Master of Data Science comprises 96 credit points structured into three parts:
Part A. Foundations for advanced data science studies (24 credit points)
These studies will provide an orientation to the field of data science at graduate level. They are intended for students whose previous qualification is not in a relevant field.
- Introduction to databases
- Algorithms and programming foundations in Python
- Introduction to computer architecture and networks
- Mathematical foundations for data science.
Part B. Core master's studies (48 credit points)
These studies draw on best practices within the broad realm of data science practice and research. You will gain a critical understanding of theoretical and practical issues relating to data science.
- Project management
- IT research methods
- Introduction to data science
- Data exploration and visualisation
- Data wrangling
- Statistical data modelling
- Data processing for big data.
Choose one of the following:
- Machine learning
- Data analysis for semi-structured data
- Malicious AI.
Part C. Advanced practice (24 credit points)
The focus of these studies is professional or scholarly work that can contribute to a portfolio of professional development. You have two options:
- Industry experience: A program of coursework involving advanced study and an industry experience studio project
- Master’s thesis: A research pathway including a thesis. If you wish to use this course as a pathway to a higher degree by research you should take this option.
