University of Adelaide

What you'll study

The curriculum builds a core foundation in mathematics and statistics before moving into applied data work. Early units cover calculus, probability and statistical inference alongside introductory programming (commonly Python and SQL) and data management concepts. Core data analytics subjects typically include database design and administration, data wrangling and transformation, data visualisation, and applied machine learning.

As you progress, you will study modules in advanced analytics, predictive modelling, time series analysis, and experimentation and causal inference. Ethics, privacy and responsible data use are woven through the program, reflecting contemporary regulatory and professional expectations. Most students complete a capstone project or industry practicum that focuses on a real-world dataset, giving hands-on experience in problem definition, pipeline development and communication of findings to stakeholders.

The degree structure supports electives and cross-disciplinary study, so you can combine analytics training with subjects from business, health, engineering or the sciences. High-achieving students may have pathways into an honours year or research-led projects.

Entry requirements

Admission is generally based on completion of an Australian Year 12 or recognised equivalent qualification. Applicants are expected to have a sound background in mathematics (mathematical methods or equivalent) and demonstrated academic achievement in relevant subjects. The University of Adelaide also accepts alternative entry pathways including recognised vocational qualifications, portfolio or interview-based entry for mature-age applicants, and articulation from partner diplomas.

Domestic applicants will be assessed against the university's standard undergraduate entry criteria. International applicants must meet the University's English language proficiency requirements and submit recognized secondary school credentials. Applicants with prior tertiary study may be eligible for credit transfer depending on subject alignment.

Career prospects

Graduates enter a wide range of roles where translating data into decisions is valued. Typical job titles include data analyst, business analyst, data scientist (with additional experience), business intelligence developer, analytics consultant and data engineer (with further technical depth).

Industry sectors that commonly hire graduates include finance and banking, government and public policy, health and biomedical research, agriculture and agritech, energy and utilities, retail and e‑commerce, and technology start-ups. The program’s practical projects and industry links also support careers in analytics strategy, product management and research-driven roles.

Why study at University of Adelaide

The University of Adelaide offers a research-informed curriculum with access to local research strengths in machine learning and data-driven sciences. Students benefit from strong industry engagement and opportunities for internships and capstone projects that connect classroom learning to workplace problems.

Located in a city with a growing tech and innovation sector, the university provides multidisciplinary study options so students can combine analytics with domain knowledge in business, health or engineering. Support services, computing facilities and industry networking events help prepare graduates for analytic roles in both Australia and internationally.