8440 modules
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AICE2008 2026-27
Computer Architecture
This module aims to give students an understanding of how a CPU works, and also the ability to implement a working CPU. The module covers basic data- and control-path design, and the implemention of an existing Instruction Set Architecture (ISA). Standard optimisations (pipelining and caches) are introduced to explain basic techniques for improving performance. The module shows how a CPU can be used as one component within a larger computational system, for example how CPUs are integrated with other devices within a modern System on Chip (SoC). -
COMP1313 2026-27
Computer Systems I
This module aims to give students an understanding of the fundamentals of computer hardware and of the principles of operation of computers and peripheral devices. In addition, the module aims to give an overview of the main families of microprocessors and their differences. Some digital electronics is also covered - with hands-on experience in the lab with a Raspberry Pi in order to better understand computer fundamentals. -
COMP1313 2025-26
Computer Systems I
This module aims to give students an understanding of the fundamentals of computer hardware and of the principles of operation of computers and peripheral devices. In addition, the module aims to give an overview of the main families of microprocessors and their differences. Some digital electronics is also covered - with hands-on experience in the lab with a Raspberry Pi in order to better understand computer fundamentals. -
COMP2323 2026-27
Computer Systems II
This module aims to introduce students to operating system internals and the general principles and practices of developing low-level software that interacts directly with hardware. -
COMP2323 2027-28
Computer Systems II
This module aims to introduce students to operating system internals and the general principles and practices of developing low-level software that interacts directly with hardware. -
PHYS6017 2028-29
Computer Techniques in Physics
This Computational Physics course is designed for students with definite interest in tackling physics problems that are only tractable through the use of computers. It covers all types of application of computers by physicists, except the control of equipment. It covers the areas of scientific computation, Monte Carlo simulations and random numbers, numerical integration, finite differencing, differential equations and signal processing. -
PHYS6017 2027-28
Computer Techniques in Physics
This Computational Physics course is designed for students with definite interest in tackling physics problems that are only tractable through the use of computers. It covers all types of application of computers by physicists, except the control of equipment. It covers the areas of scientific computation, Monte Carlo simulations and random numbers, numerical integration, finite differencing, differential equations and signal processing. -
PHYS6017 2029-30
Computer Techniques in Physics
This Computational Physics course is designed for students with definite interest in tackling physics problems that are only tractable through the use of computers. It covers all types of application of computers by physicists, except the control of equipment. It covers the areas of scientific computation, Monte Carlo simulations and random numbers, numerical integration, finite differencing, differential equations and signal processing. -
COMP3204 2028-29
Computer Vision
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. -
COMP3204 2027-28
Computer Vision
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.