MSc Artificial Intelligence

• A 2.1 Honours undergraduate degree in Computer Science, or strongly related discipline. If you studied your first degree outside the UK, see the international entry requirements.
• Applicants to this programme are expected to be competent programmers with prior practical experience in a programming language such as Java, C, Python, C++ or JavaScript.

For fees and funding options, please visit website to find out more

Alumni of Computer Science MSc programmes have gone on to work in a variety of global, commercial, financial and research institutions, including: 

• Amadeus 
• Amazon 
• Atlas 
• Avaloq 
• Barclays Capital 
• BP 
• BT Openreach 
• Capricorn Ventis 
• FactSet 
• Hailo 
• Hewlett Packard 
• Hitachi Data Systems 
• Microsoft 
• OpenBet 
• Rockstar 
• Royal Bank of Scotland 
• Sky 
• Skyscanner 
• Symantec 
• TriSystems

The Careers Centre offers one-to-one advice to all students as well as a programme of events to assist students in building their employability skills.

Compulsory

• Artificial Intelligence Practice: practical design and implementation of artificial intelligence (AI), covering techniques in the areas of AI reasoning, planning, doing and learning.  
• Artificial Intelligence Principles: foundational knowledge of artificial intelligence (AI) with an overview of AI and its philosophy. 
• Object-Oriented Modelling, Design and Programming: introduces and reinforces object-oriented modelling, design and implementation to provide a common basis of skills, allowing students to complete programming assignments within other MSc modules. The module assumes a substantial amount of prior programming experience equivalent to having completed an undergraduate degree in Computer Science.

Students should take at least one of: 

• Constraint Programming: introduces constraint-based reasoning as a powerful mechanism for knowledge representation and inference. 
• Language and Computation: covers the major aspects of natural language processing and speech understanding. 
• Machine Learning: provides a foundation in the theory behind machine learning and enables students to apply machine learning in practice to solve real-world problems. 

Optional

The following modules are optional for Computer Science programmes. Not all combinations of modules will be available for all programmes, and some modules are subject to pre-requisites being satisfied. 

Students choose two or three optional modules. In the 'Additional optional' lists, students can only take up to two of the modules in each list. 

Here is a sample of optional modules that may be offered. 

• Critical Systems Engineering 
• Data Ethics and Privacy 
• Data-Intensive Systems 
• Human Computer Interaction Principles and Methods 
• Information Visualisation
• Interactive Software and Hardware 
• Knowledge Discovery and Datamining 
• Principles of Computer Communication Systems 
• Software Architecture and Design
• Software Engineering Practice 
• Software Engineering Principles 
• User-Centred Interaction Design 

Optional modules are subject to change each year and require a minimum number of participants to be offered; some may only allow limited numbers of students (see the University's position on curriculum development). 

Additional Optional

Students may take up to two of the following: 

• Advanced Communication Networks and Systems 
• Computer Architecture
• Computer Graphics 
• Computer Security 
• Concurrency and Multi-Core Architectures
• Distributed Systems 
• Logic and Software Verification 
• Programming Language Design and Implementation 
• Signal Processing: Sound, Image, Video 
• Video Games 

Students may take up to two of the following: 

• Database Management Systems 
• Information Security Management 
• Web Technologies 

Optional modules are subject to change each year and require a minimum number of participants to be offered; some may only allow limited numbers of students (see the University's position on curriculum development). 

Dissertation

During the second semester, students work with staff to define and agree upon a topic for the extended project, which they will work on during the final three months of the course, and which finishes in a 15,000-word dissertation. Dissertation projects may be group-based or completed individually (students are assessed individually in either case). 

The dissertation typically comprises: 

• a review of related work 
• the extension of existing ideas or the development of new ideas 
• software implementation and testing 
• analysis and evaluation. 

Each project is supervised by one or two members of staff, typically through regular meetings and reviews of software and dissertation drafts. 

If students choose not to complete the dissertation requirement for the MSc, there is an exit award available that allows suitably qualified candidates to receive a Postgraduate Diploma instead, finishing the course at the end of the second semester of study.