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Computational Statistics and Machine Learning MSc

London, Bloomsbury

Deepen your expertise in machine learning and statistics through one of the most established Master’s programmes in this field. The Computational Statistics and Machine Learning MSc brings together vital knowledge in both subjects, enabling you to thrive as an expert in a data rich world. With opportunities to study modules run in collaboration with the esteemed Gatsby Computational Neuroscience Unit and Google DeepMind, this is an exceptional place to build your expertise.

UK students International students
Study mode
Full-time
UK tuition fees (2024/25)
£19,300
Overseas tuition fees (2024/25)
£37,500
Duration
1 calendar year
Programme starts
September 2024
Applications accepted
Applicants who require a visa: 16 Oct 2023 – 05 Apr 2024

Applications closed

Applicants who do not require a visa: 16 Oct 2023 – 30 Aug 2024
Applications close at 5pm UK time

Applications open

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Entry requirements

A minimum of an upper second-class UK Bachelor's degree (or international qualification of an equivalent standard) in a highly quantitative subject such as computer science, mathematics, electrical engineering, or physicals sciences. Additionally, applicants must be comfortable with undergraduate level mathematics, in particular statistics at an intermediate undergraduate level, and be proficient in linear algebra and multivariable calculus. Relevant work experience may also be considered.

The English language level for this programme is: Level 2

UCL Pre-Master's and Pre-sessional English courses are for international students who are aiming to study for a postgraduate degree at UCL. The courses will develop your academic English and academic skills required to succeed at postgraduate level.

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

Equivalent qualifications

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

International applicants can find out the equivalent qualification for their country by selecting from the list below. Please note that the equivalency will correspond to the broad UK degree classification stated on this page (e.g. upper second-class). Where a specific overall percentage is required in the UK qualification, the international equivalency will be higher than that stated below. Please contact Graduate Admissions should you require further advice.

About this degree


While machine learning is continually changing the face of industrial and societal processes, statistics enables machine learning practitioners to analyse, visualise and measure data.

This programme provides you with an opportunity to gain a deep skillset in both fields, to carve out a successful future in further research or as an industry practitioner.

Run in collaboration with UCL Statistical Science, you will benefit from world class research and teaching talents from across computer science and statistics. You will study a range of modules that enable you to gain an extensive understanding of key elements of machine learning, computer science and statistics.

With some modules taught together with the Gatsby Computational Neuroscience Unit and Google DeepMind, you will have the opportunity to learn from leading experts in many related fields. You will also undertake a substantial project, either with an industry partner or an academic researcher.

This programme will give you the skills you need to embark on further research or apply your expertise to a machine learning or statistical role in industry. By joining us, you will become part of the next generation of machine learning experts with the ability to make a tangible difference to the world around you.

Who this course is for

The Computational Statistics and Machine Learning MSc is suitable for those who have a strong background in mathematics, computer science or another science. You will also have a desire to work in a research lab, undertake a PhD, or elevate your knowledge in machine learning and computational statistics to enhance your career prospects.

Read about what it takes to study for a Master's at UCL

What this course will give you

UCL is ranked 9th globally in the latest QS World University Rankings (2024), giving you an exciting opportunity to study at one of the world’s best universities.  

UCL Computer Science is recognised as a world leader in teaching and research. The department was ranked 1st in England and 2nd in the UK for research power in Computer Science and Informatics in the UK's most recent Research Excellence Framework (REF2021) You will learn from leading experts at the forefront of computer science innovation.

UCL Computer Science graduates are highly valued as a result of the department's strong international reputation, extensive links with industry, and ideal location close to the City of London. The Centre for Computational Statistics and Machine Learning (CSML) is a major European Centre for machine learning having coordinated the PASCAL European Network of Excellence.

Coupled with the internationally renowned Gatsby Computational Neuroscience and the Machine Learning Unit, and UCL Statistical Science, the programme draws on world-class research and teaching talents. The centre has excellent links with world-leading companies in internet technology, finance, and related information areas.

The programme team takes an experimental approach to their subject, enjoying the challenge and opportunity of entrepreneurial partnerships, and placing high value on our extensive range of industrial collaborations. You will have opportunities to work on real-world projects with industry through the Department’s Industry Exchange Network (IXN).

Read about what you'll get out of a graduate programme

The foundation of your career

Graduates from the department’s machine learning programmes have been employed at major tech and finance companies. Others have gone on to pursue further study, for example at the universities of Cambridge, Helsinki, Chicago, and UCL, or a career in academia.

Employability

You will gain a variety of practical and theoretical skills in machine learning and computational statistics, providing multiple options in either research or industry.

If you are interested in pursuing a career in research or academia, the research project forms a useful step towards undertaking a PhD, as you will build on your research skills and connections with academics in the field.

Networking

UCL is proud to support innovation and link our students and research directly to real-world business applications. From internships to solving complex problems with commercial partners, UCL Engineering has a collaborative, innovative spirit at its core.

As a student and later as a graduate, you will have access to a UCL Engineering careers events programme, connecting you with employers and alumni. This programme provides invaluable insight into the reality of different roles, sectors, and current application processes.

Entrepreneurial minds thrive at UCL. For example, UCL’s IDEALondon was the first innovation centre led by a university in London, and incubates companies post-seed to reach technical and business milestones. Our academic and industrial networks provide a safe and supportive environment to grow a company.

Teaching and learning

The programme’s core curriculum is typically delivered through a combination of lectures, tutorials, and lab classes, as well as directed and self-directed learning supported by teaching materials and resources, published through each module’s online virtual learning environment. Each module employs a teaching strategy that aligns with and supports its intended learning outcomes.

You will be assessed through a range of methods across the programme, which will vary depending on any optional or elective module choices. The programme’s core curriculum is typically assessed by methods including coursework, lab work, individual and group projects, class tests, written examinations, oral assessments, and, in all cases, culminating in a final research project/dissertation.

Contact time takes various forms, including lectures, seminars, tutorials, project supervisions, demonstrations, practical classes and workshops, visits, placements, office hours (where staff are available for consultation), email, videoconferencing, or other media, and situations where feedback on assessed work is given (one-to-one or in a group).

Each module has a credit value that indicates the total notional learning hours a learner will spend to achieve its learning outcomes. One credit is considered equal to 10 hours of notional learning, which includes all contact time, self-directed study, and assessment.

The contact time for each of your 15 credit taught modules will typically include 22-30 hours of teaching activity over the term of its delivery, with the balance then comprised of self-directed learning and working on your assessments. You will have ongoing contact with teaching staff via each module’s online discussion forum, which is typically used for discussing and clarifying concepts or assessment matters and will have the opportunity to access additional support via regular office hours with module leaders and programme directors.

Your research project/dissertation module is 60 credits and will include regular contact with your project supervisor(s), who will guide and support you throughout your project. You will dedicate most of your time on this module to carrying out research in connection with your project and writing up your final report.

Modules

The Computational Statistics and Machine Learning MSc is a one-year programme.

In term 1, you will study topics in supervised learning, to gain in-depth familiarity with various classical and contemporary supervised learning algorithms, and statistical models and data analysis, to understand the exponential family of distributions and their use in the formulation of generalised linear/ additive models. You will also choose from a wide range of optional and elective topics.

In term 2, you will choose further optional topics and deepen your understanding of core principles. You will also begin preparation for your final research project/dissertation.

In term 3, you will primarily focus on your final research project/dissertation and any examinations that take place in the main examination period.

Compulsory modules





Optional modules















Please note that the list of modules given here is indicative. This information is published a long time in advance of enrolment and module content and availability are subject to change. Modules that are in use for the current academic year are linked for further information. Where no link is present, further information is not yet available.

Students undertake modules to the value of 180 credits. Upon successful completion of 180 credits, you will be awarded an MSc in Computational Statistics and Machine Learning.

Accessibility

Details of the accessibility of UCL buildings can be obtained from AccessAble accessable.co.uk. Further information can also be obtained from the UCL Student Support and Wellbeing team.

Visit us

All open days and events

Online - Open day

Graduate Open Events: Department of Computer Science

Join us for a live online information session to hear from Computer Science staff. We will cover areas such as the general admission process, careers support, and industry links/placements. There will also be an opportunity for you to ask staff and current students any questions you may have. Two sessions will run for this event. These sessions are the same and are repeated to cater to people in different time zones.

Watch on demand event

Fees and funding

Fees for this course

UK students International students
Fee description Full-time
Tuition fees (2024/25) £19,300
Tuition fees (2024/25) £37,500

The tuition fees shown are for the year indicated above. Fees for subsequent years may increase or otherwise vary. Where the programme is offered on a flexible/modular basis, fees are charged pro-rata to the appropriate full-time Master's fee taken in an academic session. Further information on fee status, fee increases and the fee schedule can be viewed on the UCL Students website: ucl.ac.uk/students/fees.

Additional costs

All full time students are required to pay a fee deposit of £2,000 for this programme. All part-time students are required to pay a fee deposit of £1,000.

Students will require a modern computer (PC or Mac) with minimum specifications 8GB RAM and 500GB SSD storage. A computer with the stated specifications is estimated to cost £500 or greater.

For more information on additional costs for prospective students please go to our estimated cost of essential expenditure at Accommodation and living costs.

Funding your studies

For more information about funding opportunities for UCL Computer Science taught postgraduate programmes, please see the department's scholarships webpage.

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

See all the ways you can fund your studies

UCL East London Scholarship

Deadline: 20 June 2024
Value: Tuition fees plus £15,700 stipend ()
Criteria Based on financial need
Eligibility: UK

UCL Friends & Alumni Association scholarship for Machine Learning

Deadline: 3 June 2024
Value: $20,000 (1 year)
Criteria Based on both academic merit and financial need
Eligibility: EU, Overseas

Next steps

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.

There is an application processing fee for this programme of £90 for online applications and £115 for paper applications. Further information can be found at Application fees.

When we assess your application we would like to learn:

  • why you want to study Computational Statistics and Machine Learning at graduate level
  • why you want to study Computational Statistics and Machine Learning at UCL
  • what particularly attracts you to this programme
  • how your academic and professional background meets the demands of this programme
  • what mathematics and statistics experience you have
  • 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.

Due to competition for places on this programme, no late applications will be considered. Students with visa requirements or applying for scholarships are advised to apply early.

Please note that you may submit applications for a maximum of two graduate programmes (or one application for the Law LLM) in any application cycle.

Choose your programme

Please read the Application Guidance before proceeding with your application.

Year of entry: 2024-2025

Apply for this course

Got questions? Get in touch

Computer Science
Computer Science

cs.pgt-admissions@ucl.ac.uk

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