University of Adelaide

What you'll study

This program combines core information technology topics with specialised AI subjects to prepare you to design, implement and evaluate intelligent systems. Study is delivered through a mix of lectures, laboratories, practical assignments and a substantial capstone or project. Typical areas of study include:

• Foundations of Information Technology — advanced software engineering, algorithms and system design that underpin reliable AI systems.
• Machine Learning — supervised, unsupervised and ensemble methods, model evaluation and feature engineering for real-world datasets.
• Deep Learning — neural network architectures, optimisation, convolutional and recurrent networks applied to vision and sequence data.
• Natural Language Processing — language models, text representation, sentiment analysis and transformer-based approaches.
• Computer Vision — image processing, object detection and semantic segmentation techniques.
• Reinforcement Learning and Decision Systems — policy learning, value functions and applications in control and robotics.
• Data Engineering and Big Data — data pipelines, databases, scalable computing and deployment of AI models to production environments.
• Ethics, Governance and Security of AI — interpretability, fairness, privacy, regulatory considerations and responsible AI practice.
• Capstone Project or Applied Research Project — an industry-linked or research-oriented project that integrates technical skills to solve a practical problem and builds a portfolio piece.

Entry requirements

Applicants are normally expected to hold a recognised bachelor degree in computer science, information technology, software engineering, electrical engineering or a closely related discipline. Applicants with a degree in another discipline may be considered if they can demonstrate relevant prior study in programming, algorithms and mathematics, or relevant professional experience.

Additional requirements commonly include:

• A satisfactory academic record in tertiary study; specific grade or GPA minimums depend on the applicant pool and faculty policy.
• Evidence of programming ability and quantitative skills — for example, coursework or professional experience in software development, data structures, statistics or linear algebra.
• International applicants must meet the University’s English language proficiency requirements; acceptable evidence includes recognised test scores or approved exemptions.
• In some cases, applicants without the formal prerequisite background may be required to complete bridging or preparatory subjects before or during the program.

Career prospects

Graduates are prepared for technical and applied roles across sectors that use AI and data-driven technologies. Common career paths include:

• Machine Learning Engineer or AI Engineer — developing and deploying models and AI services in production.
• Data Scientist or Applied Data Analyst — analysing complex datasets and delivering insights to support decision-making.
• Computer Vision or Natural Language Processing Engineer — building specialised solutions for image, video or text data.
• AI Research Assistant or Research Engineer — supporting R&D in university labs, research institutes or industry innovation teams.
• AI Consultant or Solutions Architect — advising organisations on AI strategy, design and implementation.
• Further study options — graduates may pursue a PhD in computer science, AI or related fields for research and academic careers.

Why study at University of Adelaide

The University of Adelaide offers a research-led environment with strong links between teaching and active AI research groups. Students benefit from access to computing infrastructure, supervised project opportunities and industry engagement through internships and partner projects. The program emphasises hands-on, project-based learning and prepares graduates to apply AI responsibly across domains such as health, defence, finance, agriculture and government. Located in Adelaide’s growing tech ecosystem, the University provides connections to local startups, research institutes and cross-disciplinary expertise that support career development and further study pathways.