University of Technology Sydney

37401 Machine Learning: Mathematical Theory and Applications

8cp; 3hpw x 11wks (computer lab), on campus
There are course requisites for this subject. See access conditions.


Machine learning is a field of artificial intelligence that enables machines to learn from data. This subject is designed to provide a comprehensive introduction to the fundamentals of machine learning and their applications in engineering, statistics, computer science, finance, and economics. Students gain an in-depth understanding of the techniques and applications of machine learning. In particular, the subject covers modern topics such as supervised learning, semi-supervised learning, unsupervised learning, regularisation, decision and regression trees, ensemble methods, Gaussian processes, and deep learning. The subject is designed to provide students with hands-on experience in implementing and using machine learning algorithms, as well as popular packages and libraries.

Detailed subject description.

Access conditions

Note: The requisite information presented in this subject description covers only academic requisites. Full details of all enforced rules, covering both academic and admission requisites, are available at access conditions and My Student Admin.