Data Science MSc

This course is in clearing


Course options

Select year


  • MSc Data Science, home applicant, full time

    • Home Applicant
    • Full time, 1 year
    • Pound 10200 per year
  • MSc Data Science, home applicant, part time

    • Home Applicant
    • Part time, 2 years
    • Pound 1700 per year
  • MSc Data Science, international applicant, full time

    • International Applicant
    • Full time, 1 year
    • Pound 15960 per year

What makes this course different


This programme is very popular for both home and international students. The taught components are delivered in block mode, allowing working professional at home and abroad to more easily take the course and fit it in with their busy schedules.

Student focused

Integration of concepts, techniques and applications to enhance students' knowledge and skills in the analytics pipeline.

Expert software

Open Source software tools which are widely used in the field of data science to extract value from data.

Course modules

NOTE: Modules are subject to change. For those studying part time courses the modules may vary.

Download course specification

Your future career

Your future career

The advantage of studying this programme is that it will uniquely qualify you in a field that is increasingly recognised as being central to most professional areas and for which job opportunities have been rising exponentially. Holders of an MSc in Data Science will have an advanced qualification in this area and it will prepare them for a professional or research career. Holders of this qualification will be eligible to apply for membership of the Royal Statistical Society.

Our students are professionals and graduates from a diverse range of disciplines. All are improving their career options and general expertise in this expanding market. They include data analysts from local councils, an IT teacher, an accountant, a chief software architect from Bermuda, a business manager with EDF Energy, a systems analyst, a system design analyst with Microsoft, and a psychologist. Other students have graduated from IT, sports science, neuroscience, microbiology, mathematics, physics, business, economics, law, civil engineering, and international management.

Explore the different career options you can pursue with this degree and see the median salaries of the sector on our Career Coach portal.

ACE Data Science Seminar
This course has helped me to develop my data analysis skills and understand the use of data in society. I can now program open-source software, which will give me confidence in my future career."
Maddie King

MSc Data Science

How we support your career ambitions

We offer dedicated careers support, and further opportunities to thrive, such as volunteering and industry networking. Our courses are created in collaboration with employers and industry to ensure they accurately reflect the real-life practices of your future career and provide you with the essential skills needed. You can focus on building interpersonal skills through group work and benefit from our investment in the latest cutting-edge technologies and facilities.

Career Zone

Our dedicated and award-winning team provide you with careers and employability resources, including:

  • Online jobs board for internships, placements, graduate opportunities, and flexible part-time work.
  • Mentoring programmes for insight with industry experts 
  • 1-2-1 career coaching services 
  • Careers workshops and employer events 
  • Learning pathways to gain new skills and industry insight.

Mental Wealth programme

Our Professional Fitness and Mental Wealth programme issues you with a Careers Passport to track the skills you’ve mastered. Some of these are externally validated by corporations like Amazon and Microsoft.

Our Mental Wealth programme

We are careers first

Our teaching methods and geographical location put us right up top

  • Enterprise and entrepreneurship support 
  • We are ranked 6th for graduate start-ups 
  • Networking and visits to leading organisations 
  • Support in starting a new business, freelancing and self-employment 
  • London on our doorstep

What you'll learn

This course gives you the opportunity to look at data across a wide range of subjects and sources, including finance, business, crime, health, education, planning, community, natural environment, and social media.

You will gain hands-on experience in handling data through your coursework and projects. Recent students have been analysing crime data, drawing on material similar to that used for research undertaken by our course leaders for the Metropolitan Police and Essex Police.

They have also conducted data projects for companies such as KPMG and Thames Water as well as for the Department of Health and NHS Foundation Trusts.

Course modules include Data Ecology, Quantitative Data Analysis, Spatial Data Analysis, and Advanced Decision Making, as well as your research dissertation.

The specialities of our academic team include data cleansing, data integration, data quality, data analysis, data mining, and geocomputation. Their research engages them in a variety of data from crime statistics to natural hazards, and from public health to business. It keeps them at the forefront of new developments in the field.

The cross-disciplinary approach to the subject at the University of East London means you can follow your own area of interest, enhancing your knowledge and skills under the expert guidance of your researchers.

"Our definition of data science is the science, engineering, and practice of extracting value from data that impacts business, governance, and society," says course leader, Emeritus Professor Allan Brimicombe.

"We strive to maximise the potential of all our students so they can make valuable contributions to, and enhance their careers in this new fast-growing and vibrant sector."

How you'll learn

This programme includes four taught modules and a research dissertation and is available in full-time and part-time modes. Delivery of taught modules is by block and blended learning.

Each taught module is based on one week's intensive attendance at the Docklands campus, according to an advertised calendar, usually at the beginning of each semester. Students are expected to have a laptop computer for in-class practical sessions. During the remainder of the semester, students can work on their reading, practical components (from a workbook) and coursework. Students will be supported on campus or online by tutorials. The taught modules on this programme are available to be taken as credit-bearing short courses by suitably qualified individuals.

MSc Data Science is not a computer science programme, although there is an overlap between Data Science and Computer Science. Our programme is more methodology-oriented. In other words, we focus on how to run a data project, how to develop a data solution, or how to design a data product rather than how to develop a software system/tool, though we do use software to assist data analysis and data mining while some of our students did develop tools/apps in their projects.

You need to take two modules each semester. In addition to the two weeks of intensive sessions at the beginning of the semester, you are required to attend two learning sessions every week, which are timetabled and monitored to follow the rules of the Home Office. Each such learning session is three hours so that totals six hours every week.

If you choose to accept our offer, you are agreeing to this learning agreement. If you are applying for the January entry of 2024, be aware that you will have modules of Advance Decision Making and Spatial Data Analysis in Term 2, then have modules of Data Ecology and Quantitative Data Analysis in Term 1, finally you will have your dissertation in Term 2 next year.

How you will be assessed

All the learning outcomes of the programme are assessed through:

  • Laboratory session portfolios
  • Coursework
  • Research dissertation

Campus and facilities

Docklands Campus, London, E16 2RD

Who teaches this course

This course is delivered by the School of Architecture, Computing and Engineering.

The teaching team includes qualified academics, practitioners and industry experts as guest speakers. Full details of the academics will be provided in the student handbook and module guides.