The MSc in Data Science is aimed at providing opportunities for students who wish to establish expertise and employment in data-centric, largely quantitative areas within a broad range of professional disciplines and areas of employment. A cross-disciplinary approach is therefore central to the delivery of the programme.
According to Hal Varian, Google Chief Economist, “The ability to take data - to be able to understand it, to process it, to extract value from it, to visualize it, to communicate it - that’s going to be a hugely important skill in the next decades.” It is these skills and the knowledge that underpins them that are the focus of this programme.
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.
Integration of concepts, techniques and applications to enhance students’ knowledge and skills in the analytics pipeline.
Open Source software tools which are widely used in the field of Data Science to extract value from data.
What we're researching
Data analysis, data mining and modelling, Geocomputation and mapping, data management.
Professor Brimicombe is Head of the Centre for Geo-Information Studies at UEL. He is a Chartered Geographer, an Academician of the Academy of Social Sciences, a Fellow of the Royal Statistical Society, a fellow of Royal Geographical Society, deputy chair of the National Statistician’s Crime Statistics Advisory Committee, non-executive committee member of the British Society of Criminology. He has been a Specialist Advisor to the House of Lords.
Allan's expertise focuses around cross-disciplinary applications of Geo-Information Science and Data Science. Allan pioneered the use of geo-information systems and environmental simulation modelling. His other research interests include data quality issues, spatial data mining and analysis, predictive analytics and location-based services (LBS). These have been applied to crime, health, education, natural hazards, utilities and business.
Allan’s recent projects include Olympic Games Impact Studies and Smart City studies.
Dr Yang Li is a senior research fellow at UEL. He is a fellow of Royal Geographical Society and a member of Association of Geographic Information.
Yang has rich experiences in both applications and research of Data Science and Geo-Information Science. He has expertise in data integration, data mining and data modelling. Particularly, he is a specialist in geocomputational analysis including data quality modelling and sensitivity analysis.
Yang’s recent projects include Olympic Games Impact Studies, the Prevent Project of the Home Office and TURaS.
Making a difference
UEL is one of the UK’s leading modern research universities. In the most recent Research Excellence Framework (REF), 17 per cent of our overall research submission was classified as ‘world-leading’ for its quality and impact – almost double our previous REF score. A further 45 per cent of our work was considered ‘internationally excellent’.
MSc Data Science
This course has helped me to develop my data analysis skills and in understanding the use of data in society, and guess what….I can now programme open-source software, which will give me confidence in my future career.
What you'll study
We consistently review and develop our courses and modules to ensure they are up-to-date with sector and industry graduate skills demands. Course structure, modules and options are subject to change.
- Quantitative Data Analysis (core)
- Mental Wealth: Professional Life (Data Ecology) (core)
- Advanced Decision Making - Predictive Analytics and Machine Learning (core)
- Spatial Data Analysis (core)
- Data Science Dissertation (core)
How you'll be assessed
All the learning outcomes of the programme are assessed through:
• Laboratory session portfolios
• Research dissertation
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 UEL 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.
Who will teach on this course
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.
What you'll learn
This course gives you the opportunity to look at data across a wide range of subjects and sources, including finance, crime, the environment, housing, education, demographics and social media.
You will gain hands-on experience of handling data through your course work, projects and analysis. 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 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 specialisms of our academic team include data cleansing, data integration, data mining, spatial analysis and predictive analytics and 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, Professor Allan Brimicombe.
“We strive to maximise the potential of all our students so they can make valuable to contributions to, and enhance their careers in this new fast-growing and vibrant sector.”
Your future career
The advantage of studying this programme is that it will uniquely qualify students 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, 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.