Advanced Topics in Machine Learning
| Code | School | Level | Credits | Semesters |
| COMP4132 | School of Computer Science | 4 | 20 | Autumn China |
- Code
- COMP4132
- School
- School of Computer Science
- Level
- 4
- Credits
- 20
- Semesters
- Autumn China
Summary
This module is an introduction to the advanced topics in the field of machine learning. The module covers the selected topics from the areas such as computer vision and natural language processing, with the emphasis on practical applications. We study the latest advance machine learning topics such as graph neural networks, explainable machine learning, active learning, reinforcement learning, pre-trained models, and large language models.
Target Students
Available to level 4 computer science students and selected level 3 computer science and computer science with AI students.
Classes
- One 2-hour lecture each week for 11 weeks
- One 2-hour computing each week for 11 weeks
Assessment
- 30% Coursework 1: Group programming assignment.
- 70% Exam 1 (2-hour)
Assessed by end of autumn semester
Educational Aims
The aim of this module is to introduce advance principles, techniques and applications of machine learning; to enable students to appreciate the latest machine learning algorithms and applications; to develop latest machine learning skills for practical artificial intelligent programs.Learning Outcomes
Knowledge and Understanding
• To understand the strengths and limitations of the selected advance topics in machine learning.
Intellectual Skills
• To understand and apply complex ideas to specific situations.
• To recognize the strengths and limitations of an advanced machine learning techniques.
Professional Skills
• To be able to implement the selected advanced machine learning techniques and apply them to practical applications.
• To be able to evaluate available machine learning models and analyse experimental results.
Transferable Skills
• To propose practical solutions based on the evaluation of existing techniques.
• To describe the method, evaluation process and result analysis in technical writing.
Conveners
- Dr Zheng Lu