Graduate · Data Science
Master of Data Science
Swinburne University of Technology, Melbourne, VIC, Australia
About this program
Swinburne's Master of Data Science makes the industry-based capstone mandatory rather than optional: every student works with an external client on a real business problem before graduating, not just those who opt into an industry track. High-performing students (Credit average or better) can go further and apply for the internship unit (ICT80004), which places them directly inside a company for the duration rather than working client problems from campus.
The course is structured with a graduate-certificate exit point after 8 core units, so students who need to stop partway (a job offer, a visa change, a change of plans) leave with a genuine, transcript-backed credential rather than nothing. That's a more forgiving structure than degrees where the only recognised outcome is the full masters.
Given Swinburne's engineering and computing strengths, the data science degree tends to lean toward applied, production-oriented data science, building and deploying models for real organisational use, over a purely theoretical statistics-heavy curriculum, which suits students aiming at industry data science and machine learning engineering roles rather than academic research.
Cost & duration
English test scores
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Course structure
5 terms of coursework
- 8 core units (graduate certificate exit point): programming for data science, statistical modelling, machine learning, big data systems, data visualisation, data ethics and governance
- Additional core and elective units toward the full masters (2 further core units plus 1 elective, subject to specific course version)
- Optional: Internship Project (ICT80004) for students with a Credit average or higher
- Capstone: mandatory Industry Capstone Project, delivered for an external client organisation
- Total award requirements vary by entry pathway and credit granted
- typical full-time load is 8 units/year
Admissions
Bachelor's degree in a quantitative or IT-related discipline
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