37401 Machine Learning: Mathematical Theory and Applications (University of Technology Sydney): rated 3.0/5 overall across 1 review collected on UTS Wall.
37401 is a University of Technology Sydney course taught by the Faculty of Science in Mathematical and Physical Sciences. This page brings together its handbook details and what UTS students say about it.
Review data updated 2026-10-24.
Chinese title: 机器学习：数学理论与应用
Type: Postgraduate subject
Credit points: 8
Subject area: Mathematical and Physical Sciences
Faculty: Faculty of Science
Level: Postgraduate
Handbook year: 2026
This subject offers a comprehensive introduction to machine learning, covering fundamental techniques and their applications across engineering, statistics, and economics. Students will gain a deep understanding of supervised, semi-supervised, and unsupervised learning, regularisation, decision trees, ensemble methods, Gaussian processes, and deep learning.
37401 has 1 scored review: overall 3.0/5 · usefulness 3.0 (all out of 5; higher difficulty means harder).
Sources: 1 StudentVIP review (average 3.0 stars).
The course panel on UTS Wall shows every review and discussion in full.
Q: Is 37401 worth taking?
A: Averaged over 1 review: usefulness 3.0/5, overall 3.0/5. Only a few reviews so far, so treat this as a rough guide.
Q: Which faculty teaches 37401, and when is it offered?
A: 37401 is taught by the Faculty of Science. Check the official handbook for the current year.
UTS Wall is an independent student community and is not affiliated with University of Technology Sydney.