(Full time) 2021 start
Urban Data Science and Analytics MSc

Coronavirus information for applicants and offer holders
We hope that by the time you’re ready to start your studies with us the situation with COVID-19 will have eased. However, please be aware, we will continue to review our courses and other elements of the student experience in response to COVID-19 and we may need to adapt our provision to ensure students remain safe. For the most up-to-date information on COVID-19, regularly visit our website, which we will continue to update as the situation changes www.leeds.ac.uk/covid19faqs
Overview
Our Masters degree in Urban Data Science and Analytics offers you the opportunity to gain in depth knowledge of the methods and approaches of data science and learn how to apply them in understanding cities and setting urban policy.
The course will combine technical training in the latest data science techniques – from data wrangling, to machine learning, to visualisation, and beyond – with the critical thinking needed to interrogate and understand complex urban and mobility challenges.
At the heart of this course will be a commitment to tackling the real-world challenges facing cities.
Researchers at the University of Leeds are finding novel data-driven solutions to tackle challenges such as traffic congestion, social and economic equality, pollution and competition for resources. Find out more about our Urban Analytics research at Leeds.
Course highlights
Fieldtrips in an urban context will allow you to observe first-hand how data science can be used to create and shape urban policy, and how policies in turn impact urban systems and processes.
You will work closely with external organisations and stakeholders, through co-development of creative solutions to urban problems.
You will benefit from exposure to the wide range of urban research ongoing across the University - School of Geography, Institute for Transport Studies, Leeds Institute for Data Analytics and the Alan Turing Institute, the national institute for data science and artificial intelligence.
A new seminar series featuring urban researchers and practitioners will consolidate a wider network of urban data scientists and policymakers and provide you with direct routes to the latest research, trends, and opportunities.
On completion of this course, you will have the technical skills and knowledge to secure employment in a range of organisations in roles such as a data scientist, data analyst, or software developer.
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Course content
The course combines technical training in data science with a rich exploration of urban systems and policy, enabling you to create novel data analyses that are informed by a contextual understanding of cities.
Optional modules incorporate deeper training in spatial analysis or transport training, enabling an expansion of disciplinary expertise. These modules will make you more familiar with the types of datasets and problems involved in geographic (e.g. demographic, crime, health) and transport data analyses.
Over the summer months you will work on a 60 credit research project, which brings together learning from each module, requiring you to produce a documented code workbook with a supporting 5000-word policy analysis, highlighting how data science methods can be used to inform policy interventions and decision-making.
Want to find out more about your modules?
Take a look at the Urban Data Science and Analytics module descriptions for more detail on what you will study.
Course structure
The list shown below represents typical modules/components studied and may change from time to time. Read more in our Terms and conditions.
Modules
Year 1
Compulsory modules
- Programming for Data Science 15 credits
- Analysing Cities 15 credits
- Applied Data Science for Urban Policy 30 credits
- Creative Coding on Urban Problems 15 credits
- Urban Data Science Project 60 credits
- Data Science for Cities 15 credits
Optional modules (selection of typical options shown below)
- Geographic Data Visualisation & Analysis 15 credits
- Geodemographics and Neighbourhood Analysis 15 credits
- Transport Data Science 15 credits
Learning and teaching
The course will incorporate a range of innovative modes of delivery, with a general focus on maximising time for practical, problem-based learning. For example, the ‘Creative Coding’ module will incorporate no lecture-style teaching and instead focus on problem-based learning, where you will work with other students in teams to tackle problems and datasets provided by external stakeholders. Within this module, you will be coached by teaching staff to identify novel and compelling ways to tackle the challenges and be required to present your work.
Face to face learning in workshops, small groups, drop-ins and seminars will be combined with teaching and learning delivered using interactive digital platforms that build up your skills using relevant technologies and enable effective delivery of key materials.
On this course you’ll be taught by our expert academics, from lecturers through to professors. You may also be taught by industry professionals with years of experience, as well as trained postgraduate researchers, connecting you to some of the brightest minds on campus.
Assessment
The primary mode of assessment will be through the production of code and critical analysis for the exploration of urban phenomena and problems. Some modules will focus more on qualitative analysis of urban systems, while others will incorporate aspects of team-based assessment.
Code and analyses through a personal (protected) GitHub repository will be documented, which will act as a portfolio of work for future employers on completion of the course.
Applying, fees and funding
Entry requirements
A bachelor degree with a 2:1 (hons) in a subject containing a substantial numerate component. Successful applicants will have strong grades in relevant mathematical modules.
We accept a range of international equivalent qualifications. For more information please contact the Admissions Team.
English language requirements
IELTS 6.5 overall, with no less than 6.0 in any component.. For other English qualifications, read English language equivalent qualifications.
Improve your English
International students who do not meet the English language requirements for this programme may be able to study our postgraduate pre-sessional English course, to help improve your English language level.
This pre-sessional course is designed with a progression route to your degree programme and you’ll learn academic English in the context of your subject area. To find out more, read Language for Science (6 weeks) and Language for Science: General Science (10 weeks).
If you need to study for longer than 10 weeks, read more about our postgraduate pre-sessional English course.
How to apply
Applicants are encouraged to apply as early as possible.
31 July 2021 – International applicants
10 September 2021 - UK applicants
This link takes you to information on applying for taught programmes and to the University's online application system.
If you're unsure about the application process, contact the admissions team for help.
International students
Read about visas, immigration and other information in International students. We recommend that international students apply as early as possible to ensure that they have time to apply for their visa.
Admissions policy
Faculty of Environment Taught Admissions Policy 2021
Fees
- UK: £11,250 (total)
- International: £25,500 (total)
Read more about paying fees and charges.
Brexit
Visit our Brexit page for the latest information on the effect of the UK's exit from the EU on current students and applicants to the University.
For fees information for international taught postgraduate students, read Masters fees.
Additional cost information
There may be additional costs related to your course or programme of study, or related to being a student at the University of Leeds. Read more about additional costs
Scholarships and financial support
If you have the talent and drive, we want you to be able to study with us, whatever your financial circumstances. There may be help for students in the form of loans and non-repayable grants from the University and from the government. Find out more at Masters funding overview.
Career opportunities
This course will offer you in-depth technical knowledge and skills in data science along with training in workflow practice, teamwork, and ‘hacking’ to prepare you for an exciting career in industry. An online portfolio of work developed throughout the course will be important for demonstrating skills to prospective employers.
On completion of this course, you will have the technical knowledge to secure employment in local government; companies handling spatial data (eg. supermarkets, retail); start-ups; transportation authorities and operators; urban planners; and consultancies (eg. Arup, Mott MacDonald) in roles such as a data scientist; data analyst, or software developer.
Careers support
We encourage you to prepare for your career from day one. That’s one of the reasons Leeds graduates are so sought after by employers.
We have a strong commitment to enhancing student employability. Read more about our employability support.
The University of Leeds Careers Centre also provides a range of help and advice to help you plan your career and make well-informed decisions along the way, even after you graduate. Find out more at the Careers website.