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Prof Doc 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 Professional Doctorate in Data Science (D.DataSc) is aimed at professionals who wish to enhance and/or validate data-centric, evidence-based approaches within their chosen career through a combination of taught modules and doctoral research. A cross-disciplinary approach is central to the delivery of this programme and is therefore suitable for professionals in a broad range of professional disciplines and areas of employment.

“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.” (Hal Varian, Chief Economist at Google).

The programme is unique, international, and ground-breaking in offering a Professional Doctorate qualification in Data Science. D.DataSc is an earned doctorate that allows the holder to use the title ‘Dr’.

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.

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Block mode teaching, suitable for students in employment, allowing for professional skill development.

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.

Enquire Visit UEL
1

Block mode teaching, suitable for students in employment, allowing for professional skill development.

2

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

3

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

Entry requirements

From
Degree
Minimum 2.1 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.

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Applicants are required to have relevant Work Experience

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 we're researching

Data analysis, data mining and modelling, Geocomputation and mapping, and 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 and a 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 the 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’.

What you'll study

  • Data Ecology (core)
  • Applied Research Tools and Techniques (core)
  • Research Method for Technologists (core)
  • Planning for Doctoral Research (core)
  • Work-based Project Review (core)
  • Advanced Decision Making - Predictive Analytics and Machine Learning (option)
  • Spatial Data Analysis (option)

How you'll be assessed

All the learning outcomes of the programme are assessed through:

• Laboratory session portfolios

• Coursework

• Research thesis

Course specification

How you'll learn

This programme includes six taught modules and a Research Thesis, 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 remaining of the semester, students can work on their reading, practical components (from a workbook) and coursework. Students will be supported online or on campus depending on individual students’ arrangements. The taught modules on this programme are available to be taken as credit bearing short courses by suitably qualified individuals.

What you'll learn

Our Doctoral Research course focuses on pure or applied aspects of Data Science, with each student studying data from within their main discipline or area of employment. You will learn reflective and analytic approaches to data while engaging in your own data research.

The taught elements of the course include Data Ecology, Research Methods for Technologists, Applied Research Tools and Techniques, Spatial Data Analysis, Advanced Decision Making, Work-based Project Reviews and Planning for Doctoral Research.

These elements will be reinforced by the specialist knowledge of our course leaders, whose fields of expertise includes data cleansing, data integration, data mining, spatial analysis and predictive analytics.

Their recent research has engaged them in data from crime statistics, natural hazards, public health and business, keeping them at the forefront of new developments in the field.

Our cross-disciplinary approach to the subject means that whatever your area of interest, our researchers will have the experience and expertise to enhance your knowledge and skills.

The taught modules on this course are available to be taken as credit-bearing short courses by suitably qualified individuals.

Your future career

This programme uniquely qualifies students in a field that is increasingly recognised as being central to most professional areas and research. The research component provides for a solid grounding in methods and engagement with leading-edge ideas. Job opportunities in Data Science are rising exponentially. Holders of a Professional Doctorate in Data Science will have the highest possible qualification in this area and prepare them for senior positions. They will also be eligible to apply for membership of the Royal Statistical Society.

Our students are professionals from a diverse range of areas. They include a global compliance engineer, a senior system analyst, an analytical chemist, an assistant dean at Qatar University, a SAP technology consultant from Germany, an IT trainer, a senior project manager with Diageo, an ICT manager from Ireland, a lecturer in databases from Oman, a principal consultant with Verizon, a company MD, a senior analytical consultant with TripAdvisor, a consultant with HSBC,  a software developer with HMRC, a school teacher, a marketing officer,  a data manager in Microsoft and a data analyst from New York.

All are looking to improve their career options and general expertise in this expanding market.

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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.
 

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