Data Science and Machine Learning MSc
The Data Science and Machine Learning MSc 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 tuition fees (2023/24)
Overseas tuition fees (2023/24)
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.
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. International Preparation Courses
Further information can be found on our English language requirements page.
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 Data Science and Machine Learning MSc, 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.
Who this course is for
What this course will give you
UCL is ranked 8th globally and 5th in Europe in the 2023 QS World University Rankings, giving you an exciting opportunity to study at one of world's best universities.
UCL Computer Science is recognised as a world leader in teaching and research. The department was 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 (REF2021.) You will learn from leading experts with an outstanding reputation in the field.
UCL Computer Science staff have research interests ranging from foundational machine learning and large-scale data analysis to commercial aspect of business intelligence.
Our 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.
Our extensive links to companies provides you with opportunities to carry out your research project/ dissertation with an industry partner.
We enjoy strong collaborative relationships across UCL; exposure to interdisciplinary research spanning Computer Science and Statistical Science will give you 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.
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.
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 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.
The Data Science and Machine Learning MSc 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.
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 Data Science and Machine Learning.
Fees and funding
Fees for this course
|Tuition fees (2023/24)||£18,000|
|Tuition fees (2023/24)||£35,000|
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.
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.
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 a comprehensive list of the funding opportunities available at UCL, including funding relevant to your nationality, please visit the Scholarships and Funding website.
Deadline: 8 June 2023Value: £15,000 (1 year)Criteria Based on both academic merit and financial needEligibility: UK
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 (or one application for the Law LLM) in any application cycle.
Choose your programme
Please read the Application Guidance before proceeding with your application.
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