Search for courses or information

MSc Data Science

Course overview

Start date

January 2018

September 2018

Subject area

Architecture, Computing and Engineering

Attendance

Full-time

Part-time

Learning

On campus

Course summary

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.

Contact us

If you have any questions, talk to a member of our Applicant Enquiries team on +44 (0) 20 8223 3333 or email study@uel.ac.uk.

Get in touch

Flexible

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.

Enquire Visit UEL

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’.

Maddie King

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.

Entry requirements

From
Degree
Minimum 2.2 Honours in Physical Science, Electrical/Electronic/Communication Engineering or Humanities and Social Science related subject. 

We would normally expect you to have Grade C in GCSE English and Maths. 

INTERNATIONAL

(Including European Union)

We accept a range of qualifications from across the world. Please see our country pages for information on specific entry requirements for your country.

SEE YOUR COUNTRY
Overall IELTS 6.0 with a minimum of 5.5 in all components (or recognised equivalent).

As an inclusive university we recognise that applicants who have been out of education for some time may not have the formal qualifications usually required for entry to a course. We welcome applications from those who can demonstrate their enthusiasm and commitment to study and have relevant life/work experience that equips them to succeed on the course. We will assess this from the information provided in your application (particularly your personal statement) and may ask you to attend an interview or submit a piece of work to help us decide on your eligibility for the course. Our pre-entry Information Advice and Guidance Team are able to provide further advice on entry requirements and suitability for study.

You can speak to a member of our Applicant Enquiries team on +44 (0)20 8223 3333, Monday to Friday from 9am to 5pm. Alternatively, you can visit our Information, Advice and Guidance centre. Please click here for details.

What you'll study

  • Data Ecology (core)
  • Quantitative Data Analysis (core)
  • Advanced Decision Making - Predictive Analytics and Machine Learning (core)
  • Spatial Data Analysis (option)
  • Qualitative Data Analysis (option)
  • Research Dissertation (core)

How you'll be assessed

All the learning outcomes of the programme are assessed through:

• Laboratory session portfolios

• Coursework

• Research dissertation

Course specification

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.

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.

You may also be interested in

  • Why study at UEL?

  • Open Evenings

  • Accommodation

  • Applying to UEL

  • Your offer

Related courses

Meet us in your country

Our international team travel overseas regularly to meet prospective students and attend recruitment fairs. Our academics also give regular lectures overseas and are happy to speak to prospective students. In addition, we have a large worldwide network of advisors who can provide guidance and support with applying to study at the University of East London.
 

Visit Country Pages
Global scholar students

Enquiries