University of Adelaide

What you'll study

This program builds a solid grounding in computer science fundamentals—programming, data structures and algorithms, software engineering, databases and systems—while providing focused AI and machine learning units. You will study mathematics and statistics subjects that underpin machine learning, such as discrete mathematics, linear algebra, probability and statistical inference.

• Core computer science: programming (object‑oriented and functional), algorithms and complexity, operating systems, software engineering and databases.
• Mathematics and statistics: calculus, linear algebra, probability, statistics and optimisation techniques used in learning algorithms.
• Machine learning and AI: introductory and advanced machine learning, supervised and unsupervised methods, deep learning, reinforcement learning, and probabilistic graphical models.
• Specialist AI topics: natural language processing, computer vision, robotics and perception, knowledge representation and reasoning, and explainable/interpretable AI.
• Professional practice and project work: capstone or honours project, team-based software projects, industry practicum options and coursework on ethics, privacy and responsible AI.

The degree structure typically allows students to mix core compulsory units with elective specialisations, enabling depth in AI and machine learning alongside broader computing electives or a minor from another discipline. Research-led teaching is a feature, with opportunities to engage with active research groups.

Entry requirements

Entry is usually based on a completed secondary qualification or equivalent recognised international qualification. Applicants are expected to demonstrate strong achievement in mathematics; completion of a senior high school mathematics subject (often calculus or equivalent) is normally required and specialist or advanced mathematics is recommended.

• Academic background: successful secondary school results or an equivalent qualification from a recognised awarding body.
• Mathematics prerequisite: evidence of competence in senior secondary mathematics—courses such as advanced or specialist mathematics are strongly advised.
• English language proficiency: international applicants must meet the university's English language requirements via accepted tests or equivalent qualifications.
• Alternative entry pathways: mature‑age applicants, applicants with vocational qualifications, or those who complete bridging or foundation programs may be considered.

Meeting minimum entry criteria does not guarantee admission; selection may consider the overall strength of the application and spaces available.

Career prospects

Graduates are prepared for a wide range of roles across technology and data-driven industries. Career paths commonly followed by alumni include:

• Machine Learning Engineer or Applied AI Engineer
• Data Scientist or Data Engineer
• Software Developer with a focus on intelligent systems
• Computer Vision or Natural Language Processing specialist
• Robotics engineer, automation and IoT developer
• AI consultant, product manager for AI products, or roles in government and industry policy on AI

Graduates may also pursue honours and postgraduate research (Master by Research or PhD) to move into specialised research roles or academic careers. Industry demand spans finance, healthcare, defence, agritech, manufacturing, start‑ups and public sector agencies.

Why study at University of Adelaide

The University of Adelaide offers close links to active AI research centres and industry partners, including engagement opportunities with the Australian Institute for Machine Learning (AIML). Students benefit from research-informed teaching, access to modern computing facilities and opportunities for internships, industry projects and capstone experiences that connect academic learning to real problems.

The program emphasizes ethical, safe and responsible AI alongside technical skills, preparing graduates to build systems that are both effective and socially aware. There are clear pathways to honours and research programs for students who wish to specialise further or pursue research careers.