Computing (Artificial Intelligence and Machine Learning)

Computing is a creative and wide-ranging subject that focuses on using sound underlying principles and logical thinking to design and build systems that really work.

You'll specialise in artificial intelligence and knowledge engineering, as well as machine learning and the development of computational and engineering models of complex cognitive and social behaviours.

In this course, you will learn how modern computer and communications systems function, and how they can be used and adapted to build the next generation of computing applications.

The core of this programme has been designed to give you an overview of computing. This includes an understanding of basic concepts and principles, the ability to appreciate and to adapt to changes in technology, and practical experience in applied computing.

A special emphasis of your studies will be on the fundamental principles underlying computing and on the engineering considerations involved in computing system design, implementation and usage. You will be introduced to computing architecture and hardware, and the software used to exploit them.

This course will also equip you with a strong background in discrete mathematics (logic, sets, relations and grammar), classical mathematics and statistics relevant to applications engineering and management.

Throughout the programme, you will attend laboratory and problem-solving classes, as well as completing project and design work. As the course progresses, you will study advanced techniques and modules; many of which draw on current research taking place in the Department.

At the end of your third year, you will gain valuable skills and experience by completing an industrial placement. Your study reaches Master's level in the final year, with a wide choice of optional modules and a substantial individual project on a subject of your choice.

We recommend reviewing our course page for the latest information regarding the curriculum (including core and optional modules) and course structure, as this information may be subject to periodic change.