University of Technology Sydney

37401 Machine Learning: Mathematical Theory and Applications

There are course requisites for this subject. See access conditions.


This subject introduces several machine-learning techniques and the most important mathematical foundations required in machine learning. The topics covered include time series prediction, neural networks, genetic algorithms and reinforcement learning.

The subject combines the required theory with practical applications to problems arising in statistics, data analysis and quantitative finance including algorithmic trading, portfolio optimisation and risk management.

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.