Urban Data Science and Analytics MSc
Year of entry 2023
- Start date
- September 2023
- Delivery type
- On campus
- 12 months full time
- Entry requirements
- A bachelor degree with a 2:1 (hons)
Full entry requirements
- English language requirements
- IELTS 6.5 overall, with no less than 6.0 in any component.
- UK fees
- £12,750 (total)
- International fees
- £27,750 (total)
Urban data science and analytics are critical to helping cities evolve, providing invaluable insight into urban processes, dynamics within cities, and highlighting local and global issues. This is why specialists in this field are highly sought after within the public and private sectors to help address these issues and contribute to solutions in future planning.
Our Urban Data Science and Analytics MSc 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, 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, healthy cities, and competition for resources.
This means, once you graduate, you’ll be fully equipped with the experience, technical skills, and knowledge needed to pursue a career in this area, with roles in everything from data science to software development or urban planning.
Why study at Leeds:
- Learn the latest innovations in critical areas of urban analytics with exposure to our impactful research ongoing across the university from the School of Geography, the Institute for Transport Studies, the Leeds Institute for Data Analytics, and the Alan Turing Institute, the national institute for data science and artificial intelligence which feeds directly into the course.
- Advance your skills and knowledge in key topics sought after in industry, including programming for data science, creative coding for urban problems, and analytics for urban policy.
- Conduct your own project work which will enable you to develop transferable skills as a researcher, investigating a real-world issue that explores and develops your interests.
- Tailor the course to suit your career aspirations with a selection of optional modules in areas like geographic data visualisation, geodemographics, and transport data science.
- Access specialist facilities which will complement your learning including research-grade laboratories in the Leeds Institute for Data Analytics, as well as an excellent GIS computer cluster with industry-standard software.
- Experience expert theoretical and practical teaching delivered by a programme team of academics who are actively engaged in ground-breaking research and part of the Centre for Spatial Analysis and Policy research group, Leeds Institute for Data Analytics, and the Alan Turing Institute.
- Build your industry connections through working with external organisations and stakeholders, co-developing creative solutions to urban problems.
- Put theory into practice with exciting fieldwork opportunities in an urban context, allowing 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.
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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.
In the first term, the course will introduce you to the theory and application of urban data science, through two complementary modules: Data Science for Urban Systems, and Analysing Cities. The first of these will provide a foundation in data science training, combining real-world data sets, analytics, and applications across a diverse range of contemporary urban contexts.
Analysing Cities will focus on understanding and analysing cities from a complex system perspective using an interdisciplinary approach, to consider how we plan, organise, and evaluate cities, and address future challenges. You will also be given an introduction into programming (currently using Python) on the Programming for Data Science module, parented by the School of Computing.
The second term will build and expand upon this knowledge. The Analytics for Urban Policy module will explore the key considerations in using data science across a range of urban policy areas and address how these policies result in tangible change. Field trips will enable you to observe the impact of different urban policies within diverse environments and contexts.
The Creative Coding module takes an exciting and unique ‘hackathon’ approach to deliver creative solutions to real-world challenges. Working in groups and with Industry experts, you will gain first-hand experience of applying critical and innovative thinking to evaluate and explore a range of different urban domains.
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. demographics, crime, health) and transport data analyses.
Over the summer months you will work on a 60-credit dissertation-style research project, which brings together learning from each module, requiring you to produce a documented code workbook with a supporting 5000-word practical briefing, highlighting how data science methods can be used to inform policy interventions and decision-making.
The dissertation project is one of the most satisfying elements of this course. It allows you to apply what you’ve learned to a piece of research focusing on a real-world problem, and it can be used to explore and develop your specific interests. You will also have the opportunity to work with industry partners on this project.
Example dissertation themes for Urban Data Science and Analytics MSc include:
- Urban economics
- Cities and crime
- Urban inequalities
- Transport and mobility
- Housing and real estate
- Health and wellbeing
- Smart cities
- Vulnerable populations
Fieldwork provides a great opportunity to study a fascinating subject in contrasting environments away from the University. On this programme we currently offer a UK-based fieldwork opportunity.
The list shown below represents typical modules/components studied and may change from time to time. Read more in our terms and conditions.
For more information and a full list of typical modules available on this course, please read Urban Data Science and Analytics MSc in the course catalogue
Year 1 compulsory modules
|Programming for Data Science||15|
|Data Science for Urban Systems||15|
|Creative Coding for Urban Problems||15|
|Analytics for Urban Policy||30|
|Urban Data Science Project||60|
Year 1 optional modules (selection of typical options shown below)
|Geographic Data Visualisation & Analysis||15|
|Geodemographics and Neighbourhood Analysis||15|
|Transport Data Collection and Analysis||15|
|Transport Data Science||15|
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.
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 minimal 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, laboratories, lectures, 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.
You will have access to laboratories in the Leeds Institute for Data Analytics, as well as excellent teaching facilities within the School of Geography, including a GIS computer cluster with industry-standard software.
Our Virtual Learning Environment will help to support your studies: it’s a central place where you can find all the information and resources for the School, your programme, and modules.
You can also benefit from support to develop your academic skills, within the curriculum and through online resources, workshops, one-to-one appointments and drop-in sessions.
Active research environment
You will be taught by an experienced team of academics and researchers who are actively engaged in cutting-edge research and part of the Centre for Spatial Analysis and Policy research group, Leeds Institute for Data Analytics, and the Alan Turing Institute.
The Programme Leader, Dr Vikki Houlden, is a Lecturer in Urban Data Science whose research focuses on understanding the ways in which spaces and places embody inequalities, and the social structures influencing how people relate to their environment, with particular interest in how urban landscapes impact health and wellbeing.
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.
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.
A bachelor degree with a 2:1 (hons) in a relevant subject. Those with a background in geography, urban planning, transport, or computer science, or who can demonstrate good quantitative and/or computing skills, are particularly encouraged to apply.
Applicants who do not meet the above requirement but can demonstrate several years of professional experience in a relevant field will also be considered. In this case, please contact the Admissions Team to discuss your suitability for the programme.
All applicants must have an interest in learning how to apply data science to tackle real-life urban challenges.
We accept a range of international equivalent qualifications.
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).
We also offer online pre-sessionals alongside our on-campus pre-sessionals. You could study a part-time online course starting in January, or a full-time course in summer. Find out more about online pre-sessionals.
You can also study pre-sessionals for longer periods – read about our postgraduate pre-sessional English courses.
How to apply
Applicants are encouraged to apply as early as possible.
30 July 2023 - international applicants
10 September 2023 - UK applicants
The ‘Apply’ link at the top of this page 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.
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.
University of Leeds Taught Admissions Policy 2023
This course is taught by
School of Geography
School of Computing
Institute for Transport Studies
School of Geography Postgraduate Admissions Team
UK: £12,750 (total)
International: £27,750 (total)
Read more about paying fees and charges.
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.
Find out more about our £10,000 scholarships for under-represented groups in data science.
Data science and analytics have become crucial to many industries worldwide, meaning demand for qualified specialists in this field has grown exponentially in recent years – with no signs of slowing down.
This course will teach you the in-depth technical knowledge and skills in data science along with training in workflow practice, teamwork, and ‘hacking’ that’s highly sought after by employers and will prepare you for an exciting career in industry. You'll also build an online portfolio of work developed throughout the course which will demonstrate your 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.
Plus, the University of Leeds is in the top five most targeted universities in the UK by graduate recruiters, according to High Fliers’ The Graduate Market in 2022 report.
Here’s a snapshot of positions some of our previous students on this course have secured:
- Data Analytics, Amey
- Graduate Scheme, Ernst & Young
- Data Science Internships, LIDA
At Leeds, we help you to prepare for your future from day one — that’s one of the reasons Leeds graduates are so sought after by employers. The University’s Career Centre is one of the largest in the country, providing a wide range of resources to ensure you are prepared to take your next steps after graduation and get you where you want to be.
- Dedicated Employability Officer — gain quality advice, guidance and information to help you choose a career path. From CV and cover letter writing to supporting you with job applications, our School’s dedicated Employability Enhancement Officer is on hand to help maximise your capabilities through a process of personal development and career planning.
- Employability and networking events — we run a full range of events including the School of Earth and Environment Careers Fair with employers who are actively recruiting for roles and a dedicated Industry Recruitment Day, giving you the opportunity to network with industry sponsors.
- MyCareer system — on your course and after you graduate you’ll have access to a dedicated careers portal where you can book appointments with our team, get information on careers and see job vacancies and upcoming events.
- Opportunities at Leeds — there are plenty of exciting opportunities offered by our Leeds University Union, including volunteering and over 300 clubs and societies to get involved in.
Find out more at the careers website.
Rankings and awards
Student profile: Anna Wolski
I am hoping for a career where I can use my geographical background and use the data handling skills I am learning through my masters course to make a difference in industry and for communities.Find out more about Anna Wolski's time at Leeds