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Data Science and Machine Learning MSc

Data Science 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.

Covid-19 programme updates

Due to COVID-19, there may have been updates to this programme for the 2020 academic year. Where there has been an update, these are indicated with a red alert and a link which will provide further information.

Key information

Programme starts

September 2020

Modes and duration

Full time: 1 year

Application dates

All applicants
Open: 1 November 2019
Due to the large number of applications received, this programme is closed as of 30 June 2020.

Tuition fees (2020/21)

UK/EU:
£14,320 (FT)
Overseas:
£30,400 (FT)


Note on fees: The tuition fees shown are for the year indicated above. Fees for subsequent years may increase or otherwise vary. Further information on fee status, fee increases and the fee schedule can be viewed on the UCL Students website.

Fee deposit: 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.

Location: London, Bloomsbury

Entry requirements

A minimum of an upper second-class Bachelor's degree in a quantitative discipline (such as mathematics, computer science, engineering, physics or statistics) from a UK university or an overseas, qualification of an equivalent standard. Knowledge of mathematical methods including linear algebra, calculus, probability and statistics at first-year university level is required. Depending on the modules selected, students undertake assignments that contain programming elements and prior experience in a high-level programming language (R/matlab/python) is useful. Relevant professional experience will also be taken into consideration.

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

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

International students

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.

Select your country:

About this degree

The programme comprises core machine learning methodology and an introduction to statistical science, combined with a set of more specialised and advanced options covering computing and statistical modelling. Projects are offered both within UCL Computer Science and from a range of industry partners.

Students undertake modules to the value of 180 credits.

The programme consists of three compulsory modules (45 credits), two to three optional modules (30 to 45 credits), two to three elective modules (30 to 45 credits) and a dissertation (60 credits).

Upon successful completion of 180 credits, you will be awarded a MSc in Data Science and Machine Learning.

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.

Compulsory modules

  • Applied Machine Learning (15 credits)
  • Introduction to Machine Learning (15 credits)
  • Introduction to Statistical Data Science (15 credits)
  • MSc Data Science and Machine Learning Project (60 credits)

Optional modules

Students must choose 30 to 45 credits from the optional modules, and 30 to 45 credits from elective modules.

  • Options (choose 30 to 45 credits)
  • Information Retrieval and Data Mining (15 credits)
  • Introduction to Deep Learning (15 credits)
  • Machine Vision (15 credits)
  • Multi-agent Artificial Intelligence (15 credits)
  • Reinforcement Learning (15 credits)
  • Statistical Natural Language Processing (15 credits)
  • Electives (choose 30 to 45 credits)
  • Affective Computing and Human-Robot Interaction (15 credits)
  • Applied Bayesian Methods (15 credits)
  • Bioinformatics (15 credits)
  • Computational Modelling for Biomedical Imaging (15 credits)
  • Decision and Risk (15 credits)
  • Forecasting (15 credits)
  • Graphical Models (15 credits)
  • Robot Vision and Navigation (15 credits)
  • Robotic Systems Engineering (15 credits)
  • Statistical Design of Investigations (15 credits)
  • Supervised Learning (15 credits)

Please note: the availability and delivery of modules may vary, based on your selected options as all choices are subject to timetabling constraints 

Covid-19 module updates
Due to COVID-19, there may be updates to the modules for your chosen programme of study this year. Some modules may not be available or may need to be moved to a later term or year of study. These updates are relevant for 2020-21 academic year only.  The full list of modules will be available in the module catalogue from late August.  From the first week of September, you will be invited to complete module selection from Portico, our student record system. There may need to be additional updates or changes to modules during the academic year to allow for new guidance from the UK Government and Public Health England. Your department shall keep you updated of these changes as they become available.

Dissertation/research project

All students undertake an independent research project which culminates in a dissertation of 10,000-12,000 words.

Teaching and learning

The programme is delivered though a combination of lectures, seminars, class discussions and project supervision. Student performance is assessed through a combination of unseen written examination, coursework (much of which involves programming and/or data analysis), practical application, and the research project.

Covid-19 contact hours on campus
In Term One, while campus will be open, all the learning activity for the core content of your modules will take place online – including lectures, tutorials, seminars and assessments. By “core content” we mean everything you need to learn to complete the module successfully. In addition to these online contact hours, we will be offering some face-to-face educational activities for students on campus, and we will provide alternative online activities for those students unable to join us on campus. These activities, which will include contact with academic staff, will be relevant to your programme of study may include seminars, academic and employability skills workshops, small-group or individual tutorials, lab and practice-based teaching. UK Government safety guidelines will limit the amount of ‘in person’ activity we can offer and while it will vary from programme to programme, is likely to be no more than 1-2 hours per week. This will vary across departments, particularly if your programme includes laboratory/practical/studio/workshop sessions. You will be updated with more specific details as they are available and your timetable will indicate which sessions will be on campus and which will be available online.
Covid-19 practical component updates
Due to COVID-19, there may be changes to the availability of the practical components for your chosen programme. Any updates relate only to the 20/21 academic year and may not apply to all students across the programme depending on your year of study.  Your department will keep you updated if the practical component of your programme is able to occur and/or any alternative options available.   There may need to be additional updates or changes to the practical component during the academic year to allow for new guidance from the UK Government and/or Public Health England. Your department shall keep you updated of these changes as they become available. 
Covid-19 assessment updates
There may be changes to the format of assessments for modules in this programme due to COVID-19. These will be summarised for each module on the module catalogue from 17 August 2020.   If any changes to assessments need to be made during the academic year due to updates in government guidance, these will be communicated to you as soon as possible from your department.    
Communicating further Covid-19 mitigation plans
We are continuing to follow UK Government guidance, as well as the expertise of our researchers, including specialists in health, education, human behaviour and infection prevention, to make sure UCL is as safe as possible during the COVID-19 pandemic. If it becomes necessary to make further changes to your programme as a result of new guidance/regulations, UCL and your department will communicate these as soon as this becomes clear. We will keep you up-to-date with our plans throughout term one, so you have the information you need to be able to take decisions that are right for your circumstances. Please ensure that you keep in touch with your department by regularly checking your UCL emails, Moodle courses, the Coronavirus FAQs for Students page and any UCL online groups or social media you follow.

Additional costs

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

Accessibility

Details of the accessibility of UCL buildings can be obtained from AccessAble. Further information can also be obtained from the UCL Student Support & Wellbeing team.

Funding

For more information about funding opportunities for Department of Computer Science postgraduate programmes, please see the departmental Scholarships and Funding pages: https://www.ucl.ac.uk/computer-science/study/scholarships

Scholarships relevant to this department are displayed below.

Brown Family Bursary

Note:
This scheme is now closed for 2020/21
Value:
£15,000 (1 year)
Eligibility:
UK
Criteria:
Based on both academic merit and financial need

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

Careers

Data science professionals are increasingly sought after as the integration of statistical and computational analytical tools becomes more essential to organisations. This is a very new degree and information on graduate destinations is not currently available. However, MSc graduates from across the department frequently find roles with major tech and finance companies including:

  • Google Deepmind
  • Microsoft Research
  • Dunnhumby
  • Index Ventures
  • Cisco
  • Deutsche Bank
  • IBM
  • Morgan Stanley

Employability

Students gain a thorough understanding of the fundamentals required from the best practitioners, and the programme's broad base enables data scientists to adapt to rapidly evolving goals.

Why study this degree at UCL?

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 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.

The department also enjoys strong collaborative relationships across UCL; exposure to interdisciplinary research spanning UCL Computer Science and UCL Statistical Science will provide students with a broad perspective of the field. UCL is home to regular machine learning masterclasses and big data seminars.

Department: Computer Science

Application and next steps

Applications

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 £80 for online applications and £105 for paper applications. Further information can be found at: www.ucl.ac.uk/prospective-students/graduate/taught/application.

Application deadlines

Due to the large number of applications received, this programme is closed as of 30 June 2020.

Due to competition for places on this programme, no late applications will be considered.


For more information see our Applications page.

Apply now

What are we looking for?

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.

UCL is regulated by the Office for Students.

Page last modified on 18 August 2020