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Data Science MSc

Data science brings together computational and statistical skills for data-driven problem solving, which is in increasing demand in fields such as marketing, pharmaceutics, finance and management. This MSc will equip students with the analytical tools to design sophisticated technical solutions using modern computational methods and with an emphasis on rigorous statistical thinking.

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
Part time: 2 years

Studying on a part-time basis involves spreading the taught modules over two years, but with the same teaching times as for full-time students (i.e. Mon-Fri during the daytime).

Application dates

All applicants
Open: 1 November 2019
Close: 13 March 2020

Tuition fees (2020/21)

UK/EU:
£14,730 (FT)
£7,410 (PT)
Overseas:
£31,040 (FT)
£15,530 (PT)


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.

Location: London, Bloomsbury

Entry requirements

A minimum of an upper second-class Bachelor's degree in a quantitative discipline from a UK university or an overseas qualification of an equivalent standard. Knowledge of mathematical methods and linear algebra at university level and familiarity with introductory probability, statistics and computer programming is required. 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: Standard

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 combines training in core statistical and machine learning methodology, beginning at an introductory level, with a range of optional modules covering more specialised knowledge in statistical computing and modelling. Students choosing the statistics specialisation will take one compulsory module and up to two additional modules in computer science, with the remaining modules (including the research project) taken mainly from within UCL Statistical Science.

Students undertake modules to the value of 180 credits.

The programme consists of four core modules (60 credits), four optional modules (60 credits) and a research dissertation/report (60 credits).

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

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

  • Introduction to Statistical Data Science
  • Introduction to Machine Learning
  • Statistical Design of Investigations
  • Statistical Computing

Optional modules

  • At least two from a choice of Statistical Science modules including:
  • Applied Bayesian Methods
  • Decision & Risk
  • Factorial Experimentation
  • Forecasting
  • Quantitative Modelling of Operational Risk and Insurance Analytics
  • Selected Topics in Statistics
  • Stochastic Methods in Finance I
  • Stochastic Methods in Finance II
  • Stochastic Systems
  • Up to two from a choice of Computer Science modules including:
  • Affective Computing and Human-Robot Interaction
  • Graphical Models
  • Statistical Natural Language Processing
  • Information Retrieval & Data Mining
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.  We have included these updates below:   For part-time: Year 1 optional modules include: Introduction to Machine Learning (COMP0088), Statistical Design of Investigations (STAT0029) and Statistical Computing (STAT0030), otherwise, these will be compulsory for Year 2 (part-time). Please note that Introduction to Statistical Data Science (STAT0032) cannot be taken in combination with Statistical Models and Data Analysis (STAT0028). Also note that Stochastic Methods in Finance II (STAT0018) requires that either Stochastic Methods in Finance (STAT0013) was taken in previous year or is selected for the current year. 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/report

All students undertake an independent research project, culminating in a dissertation usually of 10,000-12,000 words. Workshops running during the teaching terms provide preparation for this project and cover the communication of statistics.

Teaching and learning

The programme is delivered through a combination of lectures, tutorials and classes, some of which are dedicated to practical work. Assessment is through written examination and coursework. The research project is assessed through the dissertation and a 15-minute presentation.

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

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

Graduates from UCL Statistical Science typically enter professional employment across a broad range of industry sectors or pursue further academic study.

Employability

Data science professionals are likely to be increasingly sought after as the integration of statistical and computational analytical tools becomes essential in all kinds of organisations and enterprises. A thorough understanding of the fundamentals is to be expected from the best practitioners. For instance, in applications in marketing, the healthcare industry and banking, computational skills should should be accompanied by statistical expertise at graduate level. Data scientists need a broad background knowledge so that they will be able to adapt to rapidly evolving challenges. Recent graduates from the related Statistics MSc have been offered positions as research analysts or consultants, and job opportunities in these areas are increasing.

Why study this degree at UCL?

UCL Statistical Science has a broad range of research interests, but has particular strengths in the area of computational statistics and in the interface between statistics and computer science.

UCL's Centre for Computational Statistics and Machine Learning, in which many members of the department are active, has a programme of seminars, masterclasses and other events. UCL's Centre for Data Science and Big Data Institute are newer developments, again with strong involvement of the department, where emphasis is on research into big data problems.

UCL is one of the founding members of the Alan Turing Institute, and both UCL Statistical Science and UCL Computer Science will be playing major roles in this exciting new development which will make London a major focus for big data research.

Department: Statistical 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.

Who can apply?

The programme is accessible to students with first-degrees in a quantitative discipline (such as mathematics, statistics, physics, chemistry, biology, computer science, engineering or economics), who wish to gain advanced training in statistical analysis and computation to enable them to enter specialist employment or academic research.

Application deadlines

All applicants
13 March 2020

Please note that the admissions process is expected to be highly competitive - in the previous cycle we received over 25 applications per available place. Reaching the standard entry requirements therefore provides no guarantee that any offer will be made.


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 13 August 2020