Machine Learning MSc

The Machine Learning MSc at UCL is a truly unique programme and provides an excellent environment to study machine learning. It introduces the computational, mathematical and business views of machine learning to those who want to upgrade their expertise and portfolio of skills in this domain.

Mode of study

  • Full-time 1 year

Tuition fees

  • UK/EU Full-time: £10,450
  • Overseas Full-time: £21,700

Application date

  • All applicants: 1 August 2014

More details in Application section.

What will I learn?

Students develop an understanding of the principles underlying the development and application of new techniques in this area, alongside an awareness of, and ability to analyse the range and scope of algorithms and approaches available, and design, develop and evaluate appropriate algorithms and methods for new problems and applications.

Why should I study this degree at UCL?

UCL Computer Science is recognised as a world leader in teaching and research, and our Master's programmes have some of the highest employment rates and starting salaries.

We take an experimental approach to our subject, enjoy the challenge and opportunity of entrepreneurial partnerships and place a high value on our extensive range of industrial collaborations.

This MSc is one of the few top master programmes entirely dedicated to machine learning. It combines a rigorous theoretical academic framework along with specific knowledge of a variety of application fields to fast-track your commercial career or to prepare for PhD research.

Students undertake modules to the value of 180 credits. The programme consists of three core modules (45 credits), five optional modules (75 credits) and a research project (60 credits).

Core Modules

  • Supervised Learning
  • Programming and Mathematical Methods for Machine Learning
  • Either Graphical Models or Probabilistic and Unsupervised Learning


  • Machine Vision
  • Bioinformatics
  • Information Retrieval and Data Mining
  • Advanced Topics in Machine Learning
  • Inverse Problems in Imaging
  • Affective Computing and Human-Robot Interaction
  • Approximate Inference and Learning in Probabilistic Models
  • Applied Machine Learning
  • Computational Modelling for Biomedical Imaging
  • Evolutionary and Natural Computation


All MSc students undertake an independent research project which culminates in a dissertation ( maximum length of 120 pages) in the form of a project report.

Teaching and Learning

The programme is delivered through a combination of lectures, seminars, class discussions and project supervision. Student performance is assessed though a combination of unseen written examination, coursework (much of which involves programming and/or data analysis), practical application, and the research project.

Further details available on subject website:

Scholarships available for this department

Brown Family Bursary

This award is based on financial need.

Further information about funding and scholarships can be found on the Scholarships and funding website.

Entry requirements

A minimum of an upper second-class UK Bachelor's degree in computer science, mathematics, electrical engineering or the physical sciences, or an overseas qualification of an equivalent standard. Relevant work experience may also be taken into account. Additionally, candidates will be expected to have successfully completed as part of their first degree, one or more introductory courses covering appropriate foundation material on machine learning, or to have gained this through industrial experience.

International equivalencies

Select your country for equivalent alternative requirements

English language proficiency level: Standard

How to apply

Students are advised to apply as early as possible due to competition for places. Those applying for scholarship funding (particularly overseas applicants) should take note of application deadlines.

The deadline for applications is 1 August 2014.

Who can apply?

The programme provides a sound basis for those embarking on a career in research or development or taking up positions within industry where machine learning is currently applied or will be applied in the future; such as finance, banking and insurance, retail and web-commerce, pharmaceuticals, computer security and web search.

What are we looking for?

When we assess your application we would like to learn:

  • why you want to study Machine Learning at graduate level
  • why you want to study Machine Learning at UCL
  • what particularly attracts you to this programme
  • how your academic and professional background meets the demands of this programme
  • what programming experience you have
  • where you would like to go professionally with your degree
Together with essential academic requirements, the personal statement is your opportunity to illustrate whether your reasons for applying to this programme match what the programme will deliver.


Graduates from this programme have an excellent employment record. Within the computer science alumni network students benefit from deep corporate and academic connections. Substantial sectors of UK industry, including leading, large companies already make extensive use of intelligent systems techniques in the course of their business activities, and the UK has a number of very successful developers and suppliers of the technology.

The programme has a track record of students pursuing machine learning research degrees in domains as diverse as robotics, music, psychology, bioinformatics and universities as broad as Basel, Cambridge, Edinburgh, Nairobi, Oxford and UCL. Graduates have also found positions with multi-national companies such as BAE Systems and BAE Detica.

Top career destinations for this programme

  • Imagination Technologies, Graduate Design Engineer, 2011
  •, Programmer, 2011
  • Jive, IT Consultant, 2011
  • Cisco, Software Tester, 2011


Scientific experiments and companies now routinely generate vast databases and machine learning and statistical methodologies are core to their analysis. ML graduates have been in high demand for PhD positions across the sciences. There is a considerable shortfall in the number of qualified graduates in this area internationally. In London there are many companies looking to understand their customers better and have therefore hired ML graduates. Similarly ML graduates now work in companies in, amongst others, Germany, Iceland, France and the US in large-scale data analysis. The finance sector is also particularly interested in ML graduates, having hired several recently.

Next steps


Miss Rebecca Martin

T: +44 (0)20 7679 0481


Computer Science

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Prospectus subject

Computer Science

Faculty overview

Engineering Sciences


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