Machine Learning (934G5)
15 credits, Level 7 (Masters)
Spring teaching
On this module, you will gain the knowledge and practical experience for building and evaluating machine learning models.
The module will cover multiple learning categories including supervised learning, and a variety of algorithms will be covered (both traditional approaches and those that are state of the art, such as advanced neural networks).
The module will involve exploring the mathematics behind each algorithm as well as hands-on work (with software libraries) on real data.
Teaching
67%: Lecture
33%: Practical (Laboratory)
Assessment
100%: Coursework (Report)
Contact hours and workload
This module is approximately 150 hours of work. This breaks down into about 33 hours of contact time and about 117 hours of independent study. The 5X社区视频 may make minor variations to the contact hours for operational reasons, including timetabling requirements.
We regularly review our modules to incorporate student feedback, staff expertise, as well as the latest research and teaching methodology. We鈥檙e planning to run these modules in the academic year 2024/25. However, there may be changes to these modules in response to feedback, staff availability, student demand or updates to our curriculum.
We鈥檒l make sure to let you know of any material changes to modules at the earliest opportunity.