Taught course

Machine Learning

Royal Holloway, University of London · Department of Computer Science

Entry requirements

A 2:1 degree in Computer Science, Economics, Mathematics, Physics or other subjects that include a strong element of both mathematics and computing.

Months of entry


Course content

Machine learning has already revolutionised the user experience of millions of web users the world over, and yet the discipline is still comparatively young. In time, this form of artificial intelligence will have an even more profound impact on the way we use software and interact with computer technology. Study Machine Learning at Royal Holloway, University of London and you’ll equip yourself with a set of crucial skills to assist in the development of the next generation of search and analysis technologies.

Skills that you will acquire include the ability to:

  • develop, validate, and use effectively machine learning and statistical models
  • work with structured, unstructured, and time-series data
  • extract value and insight from data
  • work with methods and techniques such as clustering, regression, support vector machines, boosting, decision trees, and neural networks
  • develop and use universal prediction algorithms, including universal strategies for dynamic investment
  • complement predictions with provably valid measures of accuracy and reliability.
  • work with software packages such as MATLAB and R

You’ll study in one of the UK’s leading research departments, and contribute to our renowned research culture with your own Independent Project. You’ll benefit from cutting-edge research-led teaching, with the department’s research strengths including Algorithms and Applications, Machine Learning, Bioinformatics and others.

You will be taught by world-leading academics. Research in Machine Learning at Royal Holloway started in the 1990’s, at which time Vladimir Vapnik and Alexey Chervonenkis, the inventors of Support Vector Machines, were both professors here. We have developed both fundamental theory and practical algorithms that have fed into the analytics methods and techniques that are in use today. Current researchers include Alexander Gammerman and Vladimir Vovk, the inventors of conformal predictors theory, and Chris Watkins, who developed ‘Q-learning’, a work that is fundamental to planning and control.

Royal Holloway’s location close to the M4 corridor – otherwise known as ‘England’s Silicon Valley’ – gives you the chance to benefit from networking and placement opportunities with some of the country’s top technology organisations. This flexible programme is also available with a year in industry option, helping you to gain invaluable skills and experience to take into your future career.

You’ll graduate with a highly desirable Masters qualification in a rapidly expanding sector with excellent graduate employability prospects. The skills and knowledge you’ll develop will be in high demand by employers including Google, Facebook, Microsoft and Yahoo, and you'll be well prepared to pursue a rewarding career.

  • Benefit from strong industry ties, with close proximity to ‘England’s Silicon Valley’.
  • Graduate with a Master's degree offering excellent graduate employability prospects.
  • Tailor your learning with a wide range of engaging optional modules.

Qualification, course duration and attendance options

  • MSc
    full time
    12 months
    • Campus-based learningis available for this qualification
    part time
    24 months
    • Campus-based learningis available for this qualification

Course contact details

Postgraduate Admissions
+44 (0)1784 443432