Machine Learning (with a Year in Industry) – MSc

Specialism
Certification
MSc
Qualification level
MSc
Location
London
Study type
Classroom
Duration
2 years full time, 3-5 years part time
Price
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About the course

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 with a Year in Industry 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. 

By electing to spend a year in business you will also be able to integrate theory and practice and gain real business experience. In the past, our students have secured placements in blue-chip companies such as Centrica, Data Reply, Disney, IMS Health, Rolls Royce, Shell, Sociéte Générale, VMWare and UBS, among 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 includes a rewarding year in industry, 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, and you'll be well prepared to pursue a rewarding career in the field of your choosing.

  • Study in a department renowned for research excellence, ranked 11th in the UK for the quality of its research publications (Research Excellence Framework 2014).
  • Gain invaluable skills and experience with a year in industry at one of the country's leading tech organisations.
  • 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.

Course structure

Core modules

Year 1

  • Data Analysis
  • Computation with Data
  • Programming for Data Analysis
  • Machine Learning
  • On-line Machine Learning
  • Inference
  • Applied Probability

Year 2

You will spend this year on a work placement. You will be supported by the Department of Computer Science and the Royal Holloway Careers and Employability Service to find a suitable placement. This year forms an integral part of the degree programme and you will be asked to complete assessed work. The mark for this work will count towards your final degree classification.

  • Individual Project

Optional modules

In addition to these mandatory course units there are a number of optional course units available during your degree studies. The following is a selection of optional course units that are likely to be available. Please note that although the College will keep changes to a minimum, new units may be offered or existing units may be withdrawn, for example, in response to a change in staff. Applicants will be informed if any significant changes need to be made.

  • Database Systems
  • Large-Scale Data Storage and Processing
  • Methods of Computational Finance
  • Software Verification
  • Advanced Data Communications
  • Fundamentals of Digital Sound and Music
  • Semantic Web
  • Internet and Web Technologies
  • Large-Scale Data Storage and Processing
  • Service-Oriented Computing, Technology and Management
  • Business Intelligence
  • Business Intelligence Systems, Infrastructures and Technologies
  • Computational Optimisation
  • Methods of Bioinformatics
  • Visualisation and Exploratory Analysis
  • Financial Econometrics
  • Investment and Portfolio Management
  • Fixed Income Securities and Derivatives
  • Microeconometrics
  • Decision Theory and Behaviour
  • Security Technologies
  • Introduction to Cryptography and Security Mechanisms
  • Network Security
  • Computer Security (Operating Systems)
  • Security Management
  • Smart Cards, RFIDs and Embedded Systems Security
  • Digital Forensics
  • Security Testing - Theory and Practice
  • Software Security
  • Database Security
  • Cyber Security

Teaching & assessment

Assessment is carried out by a variety of methods including coursework and a dissertation. The placement is assessed as part of your degree.

Your future career

A Masters in Machine Learning with a Year in Industry at Royal Holloway, University of London offers students excellent graduate employability prospects. You’ll develop practical skills in machine Learning Techniques, making you an attractive candidate to employers and gain invaluable skills, experience and connections during your year in industry. You’ll also be well-placed to pursue PhD study, should you choose to progress your studies further.

Our recent alumni have gone on to enjoy rewarding careers in a variety of computer science-related roles, including network systems design and engineering, web development and production. Our proximity to the M4 corridor technology hub – dubbed ‘England’s Silicon Valley’ – gives students the chance to enjoy excellent networking and placement opportunities with some of the country’s top technology organisations. 

  • 90% of Royal Holloway graduates in work or further education within six months of graduating.
  • Strong industry ties help to provide placement and networking opportunities with some of the country’s leading institutions.
  • On-site College Careers Service provides help and support for students. 

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