8251 modules
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COMP6223 2029-30
Computer Vision (MSc)
The challenge of computer vision is to develop a computer based system with the capabilities of the human eye-brain system. It is therefore primarily concerned with the problem of capturing and making sense of digital images. The field draws heavily on many subjects including digital image processing, artificial intelligence, computer graphics and psychology.
This course will explore some of the basic principles and techniques from these areas which are currently being used in real-world computer vision systems and the research and development of new systems.
The objectives are to develop your understanding of the basic principles and techniques of image processing and image understanding, and to develop your skills in the design and implementation of computer vision software.
This module is taught together with COMP3204 Computer Vision. COMP6223 has higher requirements on the desired learning outcomes which will be assessed by a different set of coursework. -
COMP6223 2025-26
Computer Vision (MSc)
The challenge of computer vision is to develop a computer based system with the capabilities of the human eye-brain system. It is therefore primarily concerned with the problem of capturing and making sense of digital images. The field draws heavily on many subjects including digital image processing, artificial intelligence, computer graphics and psychology.
This course will explore some of the basic principles and techniques from these areas which are currently being used in real-world computer vision systems and the research and development of new systems.
The objectives are to develop your understanding of the basic principles and techniques of image processing and image understanding, and to develop your skills in the design and implementation of computer vision software.
This module is taught together with COMP3204 Computer Vision. COMP6223 has higher requirements on the desired learning outcomes which will be assessed by a different set of coursework. -
MATH6112 2026-27
Computer-based statistical modelling
The aim of the course is to provide a modern view of computer-based data analysis, from the statistical point of view. The course is intended for students with a solid basic background in probability, statistical methods, and computing, and who aim to build on this background. Topics are covered at a brisk pace; to make the best of this course, students can expect to put in significant self-study.
- MATH1024 and MATH2010 or equivalent maturity with Probability and Statistics
- Basic familiarity with programming in matlab or R or equivalent. -
MATH6112 2027-28
Computer-based statistical modelling
The aim of the course is to provide a modern view of computer-based data analysis, from the statistical point of view. The course is intended for students with a solid basic background in probability, statistical methods, and computing, and who aim to build on this background. Topics are covered at a brisk pace; to make the best of this course, students can expect to put in significant self-study.
- MATH1024 and MATH2010 or equivalent maturity with Probability and Statistics
- Basic familiarity with programming in matlab or R or equivalent. -
MATH6112 2025-26
Computer-based statistical modelling
The aim of the course is to provide a modern view of computer-based data analysis, from the statistical point of view. The course is intended for students with a solid basic background in probability, statistical methods, and computing, and who aim to build on this background. Topics are covered at a brisk pace; to make the best of this course, students can expect to put in significant self-study.
- MATH1024 and MATH2010 or equivalent maturity with Probability and Statistics
- Basic familiarity with programming in matlab or R or equivalent. -
MATH6112 2028-29
Computer-based statistical modelling
The aim of the course is to provide a modern view of computer-based data analysis, from the statistical point of view. The course is intended for students with a solid basic background in probability, statistical methods, and computing, and who aim to build on this background. Topics are covered at a brisk pace; to make the best of this course, students can expect to put in significant self-study.
- MATH1024 and MATH2010 or equivalent maturity with Probability and Statistics
- Basic familiarity with programming in matlab or R or equivalent. -
PSYC6109 2025-26
Concepts & Skills
This module provides a great deal of key skills training that will prepare students for a career beyond this programme, whether that be a career in academia or in the workplace. The module also encourages students to take part in lively discussions and debates, enhancing their spoken presentation and debating skills. These skills will be vital for students’ dissertations later in the year. -
PSYC6109 2026-27
Concepts & Skills
This module covers key concepts and skills relevant to working in academic and other jobs that require academic skills such as generating and presenting own research ideas and critically analysing and discussing existing research. The module provides a great deal of key skills training and encourages students to take part in lively discussions and debates, enhancing their spoken presentation and debating skills. -
PHYS1205 2025-26
Concepts in Machine Learning for Physicists
The primary goal is to provide students with necessary programming background andmathematical skills that are necessary for their degree course and developing further skills in machine learning and artificial intelligence. The emphasis throughout will be on developing insight, understanding and practical skills as well as a solid mathematical background. -
PHYS1205 2026-27
Concepts in Machine Learning for Physicists
The primary goal is to provide students with necessary programming background andmathematical skills that are necessary for their degree course and developing further skills in machine learning and artificial intelligence. The emphasis throughout will be on developing insight, understanding and practical skills as well as a solid mathematical background.