Royal Holloway, University of London

Royal Holloway, University of London

Machine Learning

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. 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. 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. - Study in a department renowned for research excellence, ranked 11th in the UK for the quality of its research publications (Research Excellence Framework 2014). - Benefit from strong industry ties, with close proximity to 'England's Silicon Valley'. - Graduate with a Masters degree offering excellent graduate employability prospects - Tailor your learning with a wide range of engaging optional modules. - Choose from a one-year programme structure or an optional year in industry.

Entry requirements

- UK Upper Second Class Honours degree (2:1) or equivalent in Computer Science, Economics, Mathematics, Physics, or other subjects that include a strong element of both mathematics and computing.

- Relevant professional qualifications and relevant experience in an associated area will also be considered.

English language requirements: IELTS with 6.5 overall and no subscore below 5.5.

Course modules

Data Analysis; Computation with Data; Programming for Data Analysis; Machine Learning; On-line Machine Learning; and one of the following: Inference; Applied Probability; Individual Project. A range of optional modules are also available.

Assessment methods

Assessment is carried out by a variety of methods including coursework and a dissertation.

Qualifications

Qualification Study mode Start month Fee Course duration
MSc Full-time September 2017 GBP 8,300 per Year 1 (Wales) 1 years
MSc Full-time September 2017 GBP 8,300 per Year 1 (Channel Islands) 1 years
MSc Full-time September 2017 GBP 8,300 per Year 1 (EU) 1 years
MSc Full-time September 2017 GBP 8,300 per Year 1 (England) 1 years
MSc Full-time September 2017 GBP 18,500 per Year 1 (International) 1 years
MSc Full-time September 2017 GBP 8,300 per Year 1 (Northern Ireland) 1 years
MSc Full-time September 2017 GBP 8,300 per Year 1 (Scotland) 1 years
MSc Part-time September 2017 GBP 8,300 per Year 1 (England) 2 years
MSc Part-time September 2017 GBP 18,500 per Year 1 (International) 2 years
MSc Part-time September 2017 GBP 8,300 per Year 1 (Northern Ireland) 2 years
MSc Part-time September 2017 GBP 8,300 per Year 1 (Scotland) 2 years
MSc Part-time September 2017 GBP 8,300 per Year 1 (Wales) 2 years
MSc Part-time September 2017 GBP 8,300 per Year 1 (Channel Islands) 2 years
MSc Part-time September 2017 GBP 8,300 per Year 1 (EU) 2 years

Campus details

Campus name Town Postcode Region Main campus Campus Partner
Royal Holloway Egham TW20 0EX South East

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