Graduate · Data Science
Master of Data Science
Adelaide University, Adelaide, SA, Australia
About this program
Adelaide University's Master of Data Science combines computer science, mathematics, and statistics with a significant capstone project (either research-based or industry-based) sitting alongside a flexible mix of core and elective courses that lets students lean toward machine learning, AI, or data engineering depending on background.
Unlike the more AI/cybersecurity-heavy Master of Computer Science, the Data Science degree keeps a stronger statistics and mathematics backbone throughout, useful for students coming from an analytics or actuarial background rather than straight software engineering. Electives can be drawn from programming, systems programming, algorithms, and distributed systems courses shared with the Computer Science program, so the two degrees overlap more than their names suggest.
Adelaide runs three intakes a year for this degree, in January, May, and September, which is unusual outside the standard February/July starts, and well suited to international students whose home academic calendars don't line up with the Australian one. Career paths include data scientist, data engineer, machine learning engineer, and business intelligence analyst.
Cost & duration
English test scores
Course structure
4 terms of coursework
Year 1, Semester 1
- Statistical Learning
- Programming for Data Science
- Data Management and Databases
- Elective1 elective
Year 1, Semester 2
- Machine Learning
- Big Data Analytics
- Elective2 electives
Year 2, Semester 1
- Data Science Capstone Project (Research or Industry-based)
- Elective1 elective
Year 2, Semester 2
- Advanced Topics in Data Science
- Elective1 elective
Admissions
Bachelor's degree in a quantitative discipline (mathematics, statistics, computer science, engineering, or similar) with a GPA equivalent to 4.5/7.0.