University of Waikato

What you'll study

The programme combines advanced coursework with project or thesis work to develop both practical and research skills in artificial intelligence. Core study areas typically include machine learning (supervised and unsupervised methods), deep learning, probabilistic modelling, optimisation, and research methods. Students also study applied topics such as natural language processing, computer vision, reinforcement learning, explainable and ethical AI, and scalable data engineering.

• Advanced Machine Learning: algorithms, model evaluation, and regularisation techniques.
• Deep Learning: neural networks, CNNs, RNNs/transformers and practical implementation.
• Probabilistic Models and Bayesian Methods: inference, graphical models and uncertainty quantification.
• Reinforcement Learning and Sequential Decision Making: policy learning and simulation-based methods.
• Applied AI Electives: natural language processing, computer vision, data mining and time-series analysis.
• Research Project or Thesis: a substantial independent project supervised by academic staff, or a taught project with industry collaboration, allowing students to apply methods to real-world problems.

Delivery includes lectures, lab work, supervised research, and project-based assessment. Students can choose pathways that emphasise coursework and industry application or that prepare for doctoral study through a stronger research component.

Entry requirements

Applicants are normally expected to hold a bachelors degree in computer science, software engineering, mathematics, statistics, data science or a closely related discipline with strong quantitative content. Candidates without a directly relevant degree may be considered if they can demonstrate equivalent knowledge and experience in programming, algorithms and mathematics (for example through professional experience or bridging coursework).

Typical requirements include evidence of academic achievement at the upper second-class honours level or equivalent, a demonstrated ability in programming and mathematical reasoning (calculus, linear algebra, probability), and a statement of intent outlining research or career goals. Applicants for the research-focused route may need to identify a potential supervisor. International applicants must meet the Universitys English language requirements.

Career prospects

Graduates of the Master of Artificial Intelligence are prepared for roles that require advanced machine learning and AI skills across private and public sectors. Common career outcomes include:

• Machine Learning Engineer or AI Engineer
• Data Scientist or Applied Data Analyst
• Research Scientist in academia or industry research labs
• Computer Vision or Natural Language Processing Specialist
• AI Consultant, product or software developer with an AI focus

Alumni work in technology companies, startups, finance, healthcare, government agencies and research institutions. The programme also provides a pathway to doctoral study for those pursuing academic or advanced research careers.

Why study at University of Waikato

The University of Waikato has a long-standing reputation in machine learning research and software development, with local groups and staff active in areas such as algorithm development, data mining and applied AI. Students benefit from hands-on teaching, access to research-active supervisors, and opportunities to work on industry-linked projects. Waikato also provides a collaborative campus environment in Hamilton with links to New Zealand industry and a supportive postgraduate community.

Practical resources available to students include computing facilities, research seminars, and access to established tools and datasets used by the machine learning community. The programmes balance of taught modules and research or project work is designed to equip graduates with both the theoretical foundations and applied experience sought by employers and doctoral programmes.