Course Details in 2026/27 Session

Module Title	LH Machine Learning
School	Computer Science
Department	Computer Science
Module Code	06 38973
Module Lead	Prof Iain Styles
Level	Honours Level
Credits	20
Semester	Semester 1
Pre-requisites
Co-requisites
Restrictions	None
Contact Hours	Lecture-33 hours Tutorial-11 hours Guided independent study-156 hours Total: 200 hours
Exclusions
Description	Machine learning studies how computers can autonomously learn from available data, without being explicitly programmed. The module will provide a solid foundation to machine learning by giving an overview of the core concepts, theories, methods, and algorithms for learning from data. The emphasis will be on the underlying theoretical foundations, illustrated through a set of methods used in practice. This will provide the student with a good understanding of how, why and when various machine learning methods work.
Learning Outcomes	By the end of the module students should be able to: demonstrate knowledge and understanding of core ideas and foundations of automated learning from data demonstrate understanding of broader issues of learning and generalisation in machine learning demonstrate the ability to apply the main approaches to unseen examples
Assessment	38973-01 : Continuous Assessment : Coursework (20%) 38973-02 : Examination : Exam (Centrally Timetabled) - Written Unseen (80%)
Assessment Methods & Exceptions	Assessment: Examination (80%), Continuous Assessment (20%) Reassessment: Examination (100%)
Other
Reading List