Electronics and Computer Science (ECS), University of Southampton

Electronics and Computer Science (ECS)

MSc Artificial Intelligence

Develop core data analysis skills and explore both traditional and state-of-the-art aspects of artificial intelligence and machine learning.

Overview

View the programme specification document for this course

This research-led MSc takes a contemporary approach and covers the fundamental aspects of traditional symbolic and sub-symbolic aspects.

The programme will give you a solid awareness of the key concepts of artificial intelligence. You will also learn the techniques that form the current basis of machine learning and data mining. You will develop a wide-ranging skill set that supports further study or that you can use in application development.

As a result of the leading research being undertaken at Southampton, the course is able to offer a wide range of options that cover state-of-the-art modern techniques, which directly reflect research directions in ECS. These include:

  • intelligent agents
  • complexity science
  • computer vision
  • robotics
  • machine learning techniques, such as kernel methods and support vector machines

To Apply

You can apply for the programme through the University of Southampton's online postgraduate application system. For more background and detailed information, see How to Apply. Please note that we belong to the Faculty of Physical Sciences and Engineering (FPSE).

Programme Structure

Twelve months, full-time.

The programme has been designed to maximise student choice by allowing you to tailor the structure to suit your own interests. You can choose areas that reflect your personal interests and work on an individual project. You will however, also take a number of compulsory modules to ensure you are exposed to key topics in all areas.

Key Facts

  • We are in the top 10% in the UK for the volume and quality of our Computer Science research (REF 2014)
  • 100% of our Computer Science research impact is world-leading or internationally excellent (REF 2014)
  • We are ranked in the UK top ten for Computer Sciences by the 2016 Guardian and Times / Sunday Times Good University Guides
  • Southampton is ranked in the top 51-100 universities for Computer Science in the 2015 QS World Rankings
  • Southampton University has pioneered many of the most important advances in computer science and web technology of the past 10 years

Entry requirements

Honours Degree:

Our normal entry requirement is an upper second-class honours degree or higher (or equivalent) in a related discipline, such as mathematics, physics, engineering or computer science.

English Language Requirements:

If English is not your first language, you will be required to pass an approved English test. We normally ask for IELTS 6.5 overall with at least 6.0 in each competency. For information on other accepted English language tests, please visit www.southampton.ac.uk/admissions_language.

International Qualifications:

We welcome applications from international students. For information on applying, visit the International Office website.

Selection Process:

All individuals are selected and treated on their relative merits and abilities in line with the University's Equal Opportunities Policy. Disabled applicants will be treated according to the same procedures as any other applicant with the added involvement of the Disability Office to assess their needs. The programme may require adaptation for students with disabilities (eg hearing impairment, visual impairment, mobility difficulties, dyslexia), particularly the practical laboratory sessions, and we will attempt to accommodate students wherever possible.

Modules

Year 1

Semester 1

Optional Modules

Modules not in Semesters

Compulsory Modules

Learning

To Apply

You can apply for the programme through the University of Southampton's online postgraduate application system. For more background and detailed information, see How to Apply. Please note that we belong to the Faculty of Physical Sciences and Engineering (FPSE).

Related programmes

Career opportunities

This programme provides an excellent platform for further research in either industry or academia.

Graduates from our MSc programme are employed worldwide in leading companies at the forefront of technology.  ECS runs a dedicated careers hub which is affiliated with over 100 renowned companies like IBM, ARM, Microsoft Research, Imagination Technologies, Nvidia, Samsung and Google to name a few.  Visit our careers hub for more information.

  • Academia
  • Bioinformatics
  • Chemoinformatics
  • Financial services
  • Web applications

Pre-course reading lists

People on the MSc come from a variety of backgrounds, however you are expected to have some numerate and mathematical ability, and exposure to programming is strongly desirable. Many key modules require some programming aspects and it will help if you are familiar with at least the basics. A useful tool in AI and machine learning is MATLAB, which is a professional mathematical language. It is available at the university, but expensive to buy a single license. We therefore do not expect you to do this, however there is an open source package Octave for which the language and basic functionality is very similar. Some exposure to this before you start may help you out a little in some of the courses (and it is not a bad skill to have in any case!).

Refreshing some linear algebra and basic probability aspects would also help you when you start, as unsurprisingly these are some of the common mathematical tools which are used in the field. No experience of AI or machine learning is necessary, however a good idea of both disciplines could be gained from the following two books, and these are thus recommended (The Foundations of AI course uses the first, and the ‘Advanced Machine Learning’ course which everyone is strongly encouraged to take uses the second):

  • Artificial Intelligence: A Modern Approach, Stuart Russel, Peter Norvig; Pearson Education; 2 edition; ISBN-10: 0130803022, ISBN-13: 978-0130803023
  • Pattern Recognition and Machine, by Christopher M. Bishop; Springer-Verlag New York Inc.; New Ed edition; ISBN-10: 0387310738, ISBN-13: 978-0387310732