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Computational Statistics and Machine Learning MSc

London, Bloomsbury

Enhance your expertise in machine learning and statistics with one of the most established Master's programmes in this field. Our one-year Computational Statistics and Machine Learning MSc combines essential knowledge from both subjects, preparing you to excel in a data-rich world. With opportunities to study modules in collaboration with the prestigious Gatsby Computational Neuroscience Unit and Google DeepMind, this MSc is an exceptional opportunity to build your skills and expertise.

UK students International students
Study mode
Full-time
UK tuition fees (2025/26)
£20,500
Overseas tuition fees (2025/26)
£39,800
Duration
1 calendar year
Programme starts
September 2025
Applications accepted
Applicants who require a visa: 14 Oct 2024 – 04 Apr 2025

Applications closed

Applicants who do not require a visa: 14 Oct 2024 – 29 Aug 2025
Applications close at 5pm UK time

Applications open

Apply for this course

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


If you're aiming to excel in machine learning and statistics, whether in research or an industry role, this programme is for you. On this MSc, you'll develop deep expertise in both fields — essential for analysing, visualising, and measuring data.

Collaborating with UCL Statistical Science, this Master's leverages world-class research and teaching across computer science and statistics. You will study a range of modules that cover key elements of machine learning, computer science, and statistics.

With opportunities to learn from leading experts through modules taught alongside the Gatsby Computational Neuroscience Unit and Google DeepMind, you will gain cutting-edge knowledge. Additionally, you will undertake a substantial project with either an industry partner or an academic researcher.

This programme prepares you for a successful future in further research or as a machine learning or statistics practitioner, positioning you as part of the next generation of experts making a tangible impact on the world.

Who this course is for

This MSc programme is ideal for you if you have a strong background in mathematics, computer science or another science. 

It is particularly suitable for those with a desire to work in a research lab, undertake a PhD, or elevate knowledge in machine learning and computational statistics to enhance their career prospects.

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

What this course will give you

This programme offers you the following benefits and opportunities. 

Recognition from a top-ranked university: UCL is consistently ranked among the best universities globally (ranked 9th in the QS World University Rankings 2025), providing you with a prestigious qualification that is highly regarded by employers worldwide. UCL was also named The Times and Sunday Times University of the Year 2024.

High-quality education from leading experts: Learn from world-renowned academics who are at the forefront of computer science innovation. UCL Computer Science is recognised for its research excellence, ranked first in England and second in the UK for research power in Computer Science and Informatics in the UK's most recent Research Excellence Framework (REF 2021). 

Excellent research and industry links: 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.

Entrepreneurial and industry partnerships: 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. 

Enhanced research skills: The research-based components of the programme will equip you with strong analytical and problem-solving abilities, preparing you for potential doctoral studies or research-intensive roles in industry.

Real-world experience through project work: Apply your knowledge and skills in practical settings with a substantial research or engineering project. Many of these projects are conducted in collaboration with industry partners, giving you valuable hands-on experience and industry insights. 

Strong employability with high employment rates and starting salaries: Our graduates are highly sought after in the job market, thanks to UCL's strong reputation and the skills gained during the programme. You'll be well-prepared to enter a variety of high-demand roles in machine learning.

Read about what you'll get out of a graduate programme
Making an impact
UCL Portico building with welcome sign between columns.

Case study: Artificial Intelligence in court

We trained an artificial intelligence system that predicted court case verdicts to 79% accuracy.

The foundation of your career

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

You’ll have regular opportunities to connect, collaborate and network with peers and members of academia and industry as part of your Master’s, particularly through collaborative project work and research seminars.

  • As a student and later as a graduate, you will have access to the UCL 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. 
  • UCL has a large number of clubs and societies, which can be an effective way to connect with peers who share similar interests and career goals. 
  • Be part of a university where entrepreneurial minds thrive. Our academic and industrial networks provide a safe and supportive environment if you want to grow your own company. 
  • London’s Tech scene is vibrant and has regular networking events.

Teaching and learning

This programme is delivered through a combination of lectures, tutorials, lab classes, and self-directed learning supported by online resources.

You will be assessed through various methods, including coursework, projects, exams, and a final research project/dissertation.

For full-time students, typical contact hours are approximately 12-16 contact  hours per teaching week, depending on module selections and timetabling. These contact hours include lectures, seminars, workshops, and tutorials, office hours and other events.

Outside of these sessions, students are expected to engage in significant self-directed study and complete assessments. Formal teaching and self-directed study together amount to a workload comparable to a full-time job, roughly 35-40 hours per week in total.

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










Machine Learning Seminar




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. Further information can also be obtained from the UCL Student Support and Wellbeing Services team.

Fees and funding

Fees for this course

UK students International students
Fee description Full-time
Tuition fees (2025/26) £20,500
Tuition fees (2025/26) £39,800

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

For Full-time and Part-time offer holders a fee deposit will be charged at 10% of the first year fee.

Further information can be found in the Tuition fee deposits section on this page: Tuition fees.

Students will require a modern computer (PC or Mac) with minimum specifications of 8GB RAM and 500GB SSD storage with a camera and microphone. However, we recommend at least 16GB RAM and 0.5-1 TB SSD storage. If you are considering undertaking a machine learning project, there will be computational capability available to you from within the Computer Science department, but you may nevertheless find it helpful to have a capable GPU in addition to the above.

UCL’s main teaching locations are in zones 1 (Bloomsbury) and zones 2/3 (UCL East). The cost of a monthly 18+ Oyster travel card for zones 1-2 is £114.50. This price was published by TfL in 2024. For more information on additional costs for prospective students and the cost of living in London, please view our estimated cost of essential expenditure at UCL's cost of living guide.

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: 26 June 2025
Value: Tuition fees plus £16,000 stipend ()
Criteria Based on financial need
Eligibility: UK

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. 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: 2025-2026

Apply for this course

Got questions? Get in touch

Computer Science
Computer Science

cs.pgt-admissions@ucl.ac.uk

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