Master of Data Science

The Master of Data Science at Adelaide University is a two-year coursework degree for people who want to work with data at a professional level. You'll study statistics, programming, machine learning and database systems, then apply them to real problems. The degree sits at AQF level 9, which means it builds on a bachelor qualification and expects you to handle advanced material. Most students come from mathematics, statistics, computer science, engineering or economics, but the course also suits graduates from other fields who have strong quantitative skills and want to move into data science.

How the degree is structured

Australian master's degrees are organised into units of study, each worth a set number of credit points. You'll typically complete 16 units over two years, or 12 units if you receive credit for previous study. The academic year runs across semesters, with some units offered in summer or winter school. Core units cover statistical modelling, data wrangling, machine learning and computing for data science. You then choose electives from areas such as biostatistics, econometrics, spatial data or data engineering, depending on your interests and the school's offerings.

Most students finish with a capstone project or a research thesis. A capstone usually involves a real dataset from an industry partner or a research group, and you present your findings at the end of the degree. If you're considering a PhD, the research thesis option is the better path because it gives you experience in independent investigation. Some students also take an industry internship as part of their elective choices, which counts towards their degree and gives them Australian work experience.

The skills you gain are practical: cleaning and reshaping messy data, choosing the right statistical model, writing code that others can read, and explaining your results to people who aren't statisticians. You'll use tools like R, Python and SQL, and you'll learn to work in teams on projects with deadlines. The degree suits people who like solving puzzles with numbers and want a job that combines computing with statistical thinking.

Adelaide University has research strengths in health, agriculture, defence and environmental science, so data science projects often connect to those areas. The Australian data science job market is strong in banking, government, health and mining, and graduates with a master's degree are eligible for the Temporary Graduate visa (subclass 485) post-study work stream. While you study, your visa allows you to work up to 48 hours per fortnight, which can help you gain local experience. English requirements for international students are set at IELTS 6.0–6.5 overall for most coursework master's degrees, but you should check the official page for the exact score this course requires. Tuition fees are published on the CRICOS register under course code 115904D.

• Data scientist — working in banks, insurers, telecommunications companies and retailers to build predictive models and analyse customer behaviour.
• Data analyst — employed across government agencies, health services and consulting firms to turn data into reports and recommendations.
• Machine learning engineer — building and deploying models in tech companies, startups and research organisations.
• Biostatistician — supporting clinical trials, public health research and hospital analytics in the health sector.
• Quantitative analyst — working in investment banks, superannuation funds and financial regulators.
• Data engineer — designing data pipelines and infrastructure for organisations that handle large volumes of data.
• Research data scientist — supporting university research groups and CSIRO projects in fields such as agriculture, environment and defence.