Data Science and Machine Learning MSc

London, Bloomsbury

The MSc Data Science and Machine Learning at UCL brings together computational and statistical skills and machine learning for data-driven problem solving. This rapidly expanding area includes deep learning, large-scale data analysis and has applications in e-commerce, search/information retrieval, natural language modelling, finance, bioinformatics and related areas in artificial intelligence.

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 closed

Notification

Application closes at 17:00 GMT.

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, engineering, physicals, or statistics. Additionally, applicants must have knowledge of mathematical methods including linear algebra, calculus, probability and statistics at least at the level taught in the first year of a UK university undergraduate programme in the mathematical sciences. Relevant work experience may also be considered. Depending on the optional modules selected, students undertake assignments that contain programming elements and prior experience in a high-level programming language (e.g., Python) is useful.

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 Data Science and Machine Learning, you will develop an understanding of core machine learning methodologies and statistical science, combined with a set of more specialised and advanced topics covering computing and statistical modelling. 

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

Who this course is for

Not applicable.
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 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.

UCL Computer Science staff have research interests ranging from foundational machine learning and large-scale data analysis to commercial aspect of business intelligence. Our extensive links to companies provide students with opportunities to carry out the research project with an industry partner.

UCL Computer Science enjoys strong collaborative relationships across UCL; exposure to interdisciplinary research spanning Computer Science and Statistical Science will provide students with a broad perspective of the field.

UCL Computer Science is home to regular machine learning masterclasses and big data seminars.

The programme team takes 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.

The foundation of your career

Alumni from the department’s machine learning programmes have been employed at major tech and finance companies including, Google Deepmind, Microsoft Research, Dunnhumby, Index Ventures, Cisco, Deutsche Bank, IBM, and Morgan Stanley. Others have gone on to pursue further study or a career in academia.

Employability

The programme is designed to teach you key skills in fundamental and applied aspects of machine learning and data analysis such that you will be able to transition smoothly to an analytic role in the AI-related industries or such that you will be able to embark upon a further course of research-based study such as a doctoral programme.

Accreditation

Not applicable.

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 Data Science and Machine Learning is a one-year programme.

In term 1, you will study introductory machine learning, to become familiar with the conceptual landscape of machine learning and develop practical skills to solve real world problems using available software. You will also choose from a wide range of optional and elective topics.
In term 2, you will study applied machine learning, which will cover some of the mathematics and techniques behind basic data analysis methods. 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 Data Science 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: UCL Computer Science

Join us for a virtual information and Q&A session with UCL Computer Science. We will have a brief overview from the Head of Department with the opportunity to ask questions. This will be followed by breakout sessions in MSc subject group areas. We will have Programme Directors, Admissions staff and students available to answer your questions about studying an MSc programme in our department. The event will take place via Zoom meetings.

Online - Open day

Spring into STEM - Bioengineering of vaccines - Virtual Lecture Series

Spring Into STEM: Bioengineering of vaccines will be given by Dr Steffi Frank and is the last of six presented by UCL Biochemical Engineering, part of the Spring into STEM webinars from UCL Engineering.

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.

Scholarships relevant to this department are displayed below.

Brown Family Bursary

Deadline: 9 June (application via the Masters Funding Awards)
Value: £15,000 (1 year)
Criteria Based on both academic merit and financial need
Eligibility: UK

DeepMind Scholarship (Computer Science)

Value: UK Home fees, maintenance grant, plus travel and equipment grants (1 year )
Criteria Based on financial need
Eligibility: UK

Next steps

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 access your application we would like to learn:

  • why you want to study Data Science at graduate level
  • why you want to study Data Science at UCL
  • what particularly attracts you to the chosen programme
  • how your academic and professional background meets the demands of this challenging programme
  • 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.

Candidates are requested to begin their personal statement with a note on the formal (accredited) results which they have obtained in each of the following areas: Linear Algebra, Calculus, Probability and Statistics. Candidates should do this under 4 separate headings, one for each area, under which they note the modules/courses in which the content in that area was covered, the grade achieved on those modules/courses, and the key topics covered in those modules/courses.

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.

UCL is regulated by the Office for Students.

This page was last updated 28 Sep 2021