MSc Computational Statistics and Machine Learning teaches advanced analytical and computational skills for success in a data rich world. Designed to be both mathematically rigorous and relevant, the programme covers fundamental aspects of machine learning and statistics, with potential options in information retrieval, bioinformatics, quantative finance, artificial intelligence and machine vision.

The programme is organised by the Centre for Computational Statistics and Machine Learning (CSML) - a major European Centre for Machine Learning and was scientific coordinator of the PASCAL2 European Network of Excellence. Coupled with the internationally renowned Gatsby Computational Neuroscience and Machine Learning Unit, and the prestigious Department of Statistical Science, the programme draws on world class research and teaching talents.


MSc Computational Statistics and Machine Learning comprises 8 taught modules and a Dissertation. Of the taught modules, 2 are core modules, with either 5 option and 1 elective module, or 4 option and 2 elective modules, or 3 each of option and elective modules.

Syllabus content for all postgraduate modules can we found in the Department of Computer Science 2018/19 online syllabus pages.


Programme diet (modules available to you)

Your programme has a set curriculum (also called a diet) which prescribes in what combinations modules can be taken, any restrictions on doing so, and how much credit can and must be taken. The programme information pages show which modules form part of each programme, with links to descriptions and module syllabus information. Modules within a programme can be core, optional, or elective, which reflects whether they must be taken or are optionally taken.

Core modules

Core modules are fundamental to your programme’s core curriculum and are mandatory. You will automatically be registered on your programme's core modules, so will not have to select them. You are guaranteed a place on modules that are core for your programme. There will be no timetable clashes between core modules within a programme.

Optional modules

Optional modules are usually closely related to the programme's core curriculum and you will be able to choose which to take; choices are usually made from within specific groups (for example, choose two optional modules from one group and three from another, etc.) You are not guaranteed a place on optional modules as space is strictly limited. We allocate places on a first come, first serve basis, with preference given to Computer Science students over those of other departments. Bear in mind that some modules have prerequisites that must be met in order to be eligible for a place (see the module syllabus for information.)

Elective modules

Elective modules are usually not specifically related to the programme's curriculum. There is no guarantee of being accepted onto an elective module; they are core and/ or optional on other programme diets, so students on those programmes will be given priority. As with optional modules, some electives have prerequisites that must be met.


Deciding which modules to select

The programme information pages show which modules form part of each programme, with links to detailed module syllabus information and reading lists. You may be able to virtually audit lectures for some modules to get a sense of how the module is delivered. You can look up the timetable for each module via the common timetable to get a sense of the timetable that would eventuate from your module choices, which is an important consideration when making your final choices; you should aim to achieve a timetable that is feasible and will not stretch you too thinly.

Bear in mind that places on optional and elective modules are not guaranteed, so you might not always be able to take all your first choices. In that case, it is a good idea to have a second preference in mind.

If you need guidance with choosing which modules to select then please contact your Programme Director or the Departmental Tutor.

A minimum of an upper second-class UK Bachelor's degree in a highly quantitative subject such as computer science, statistics, mathematics, electrical engineering or the physical sciences, or an overseas qualification of an equivalent standard. Relevant work experience may also be taken into account. Students must be comfortable with undergraduate-level mathematics; in particular it is essential that the candidate will have knowledge of statistics at an intermediate undergraduate level. Candidates should also be proficient in linear algebra and multivariable calculus.

English Language Requirements

If your education has not been conducted in the English language, you will be expected to demonstrate evidence of an adequate level of English proficiency.

The English language level for this programme is: Good

Further information can be found on our English language requirements page.

International students

Country-specific information, including details of when UCL representatives are visiting your part of the world, can be obtained from the International Students website.

2019/20 Tuition Fees

UK/EU Fees (FT):

£13340 for 2019/20

UK/EU Fees (PT):

N/A for 2019/20

Overseas Fees (FT):

£28410 for 2019/20

Overseas Fees (PT):

N/A for 2019/20

Funding Opportunities

The Department of Computer Science is offering Excellence Scholarships to our taught postgraduate students. To check your eligibility and to apply, see the Computer Science Excellence Scholarship application form.

For a comprehensive list of the funding opportunities available at UCL, including funding relevant to your nationality, please visit the Scholarship and Funding website.

Tuition Fee Deposit

This programme requires that applicants firmly accepting their offer pay a deposit. This allows UCL to effectively plan student numbers, as students are more demonstrably committed towards commencing their studies with us.

For full details about the UCL tuition fee deposit, please see the central UCL pages.

Tuition fee deposits within the Department of Computer Science are currently listed as:

UK/EUOverseas
Full-time*Part-timeFull-time*Part-time
£2000£1000£2000£1000
*only applicable where part-time is an available mode of study

Top graduate destinations:

Top graduate roles:

Further study destinations:

  • DeepMind
  • Google
  • Salesforce
  • YoungGov
  • Software Developer
  • Accountant
  • Financial Consultant
  • Actuary
  • UCL
  • University of Cambridge
  • MIT

Average starting salary £47,500 (Graduate Surveys, January 2015).

Programme Administrator

Abena Adi

Office: 5.22, Malet Place Engineering Building

Telephone: +44 (0) 20 7679 7937

Email: advancedmsc-admissions@cs.ucl.ac.uk

Click here for more information

To apply now click here.

This MSc receives many more applications than it has places available and the admissions process is competitive. It may therefore take longer than the Admissions stated 6 weeks for a decision to be made and communicated. Applicants are advised to apply as early as possible due to the competition for places.

Those applying for scholarship funding (particularly overseas applicants) should take note of application deadlines.

Deadline 14th June 2019.