Computational Statistics and Machine Learning MSc

London, Bloomsbury

The MSc Computational Statistics and Machine Learning at UCL 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, quantitative finance, artificial intelligence, and machine vision.

UK students International students
Study mode
Full-time
UK tuition fees (2022/23)
£16,500
Overseas tuition fees (2022/23)
£32,100
Duration
1 calendar year
Programme starts
September 2022
Applications accepted
All applicants: 18 Oct 2021 – 31 Mar 2022

Applications open

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.

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

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. International Preparation Courses

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

As a student on the MSc Computational Statistics and Machine Learning, you will learn the foundational principles of machine learning and statistics and gain the practical experience needed by employers in this area. You will have the opportunity to develop skills by tackling problems related to industrial needs or to leading-edge research.

Students on this programme will take modules to the value of 180 credits, on successful completion of which they will be awarded MSc in Computational Statistics and Machine Learning.

Who this course is for

Not applicable.

The programme is suitable for students with good analytical abilities. Graduates will benefit directly from our excellent academic and industrial links, either by embarking on further study in a leading centre in machine learning/statistics or by taking up a place in industry, in information retrieval, finance or bioinformatics.

What this course will give you

  • UCL received the highest percentage (96%) for quality of research in Computer Science and Informatics in the UK's most recent Research Excellence Framework (REF2014).
  • UCL Computer Science graduates are highly valued as a result of the department's strong international reputation, strong 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, enjoy the challenge and opportunity of entrepreneurial partnerships, and place a high value on our extensive range of industrial collaborations.

The foundation of your career

Alumni 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

The programme is designed to train students in both the practical and theoretical sides of machine learning. A significant grounding in computational statistics is also provided.

Teaching and learning

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 a variety of forms, including lectures, seminars, tutorials, project supervisions, demonstrations, practical classes and workshops, visits, placements, office hours (where staff are available for consultation), email, videoconference, 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 on average to achieve its learning outcomes. One credit is typically described as being 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 (classroom based and/ or online) 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

Full-time

The MSc Computational Statistics and Machine Learning 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.

Part-time

Not applicable.

Flexible

Not applicable.

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 is subject to change.

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.

Fieldwork

Not applicable.

Placement

Not applicable.

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 & Wellbeing team.

Online - Open day

Graduate Open Events: Applying for Graduate Study at UCL

Fees and funding

Fees for this course

UK students International students
Fee description Full-time
Tuition fees (2022/23) £16,500
Tuition fees (2022/23) £32,100

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 laptop (PC or Mac). The minimum specifications should be 8GB RAM and 500GB SSD storage. The recommended specification is 16GB RAM, 0.5/1TB SSD storage and a dedicated high end graphics card. A laptop with the stated specifications will cost approximately £500-£1000.

Some students run Linux on their PCs while others run Windows with Linux Virtual Machines installed.

Not applicable.

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 Department of 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.

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 in any application cycle.

We recommend that you submit your application as soon as possible. The programme may remain open if places are still available after 31 March 2022 and will be closed as soon as it is full or by 30 June 2022.

UCL is regulated by the Office for Students.

This page was last updated 28 Sep 2021