Urban Data Science and Analytics MSc

Course overview

Please note: applications for this course open on the 1^st October 2024.

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.
• 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.
• 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.
• 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.

Related courses

Environmental Data Science and Analytics MSc

This Masters degree is a great fit for students interested in environmental processes and using data-driven solutions to provide insight for the future of our planet at multiple scales. Like our Urban Data Science and Analytics MSc, you’ll build skills in data wrangling, machine learning, data analysis, visualisation and creative coding – but with a broader perspective on the environment as a whole, using a variety of data from multiple ecosystems.

Air Quality Solutions with Data Science MSc

Take a data science approach to a broad range of air quality-related topics, including emissions, monitoring, modelling, pollution exposure, health impacts and policy and economic appraisal. From Clean Air Zones to managing indoor sources of air pollutants, you’ll use research-led pollution-monitoring techniques to critically evaluate the impact of these interventions.

Course details

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.

Semester 1

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'll also be given an introduction into programming (currently using Python) on the Programming for Data Science module, parented by the School of Computer Science.

Semester 2

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'll 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 (eg demographics, crime, health) and transport data analyses.

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.

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

Compulsory modules

Programming for Data Science – 15 credits

Develop a strong foundation in programming to enhance your data science skill set. This module is designed to give those with little or no programming experience a firm foundation in programming for data analysis and AI systems, recognising a diversity of backgrounds. The module will also fully stretch those with substantial prior programming experience (e.g., computer scientists) to extend their programming and system-building knowledge through self-learning supported by on-line courseware.

Data Science for Practical Applications – 15 credits

Gain experience and acquire foundational knowledge in data science. From being introduced to concepts in data handling, exploratory data analysis, to machine learning and visualisation. You'll have opportunities to work with a variety of spatial and spatiotemporal datasets relating to practical problems in the real world, including multiple environments.

Creative Coding for Real-World Problems – 15 credits

This will be your chance to enhance your creativity and develop your technical skills in relation to variety of mixed environments. Supported by visiting academics and industry partners, you’ll work in groups to derive solutions that are novel and insightful through application of programming skills.

Analysing Cities – 15 credits

You’ll explore urban systems and urban policy, primarily focusing on concepts of urban complexity (along themes such as mobility, housing, environment, health, etc). The module will encourage critical reflection on urban systems, and how their design and policies promote different outcomes.

Analytics for Urban Policy – 30 credits

This module will expose you to the latest uses of data science for understanding cities and setting urban policy, explore technical, procedural and ethical challenges in using data science in urban policymaking, and address how urban policy results in tangible change in real-world cities. You'll be taught through a mix of lectures, workshops, and fieldwork, which will expose students to the impact of different urban policies within diverse environments.

Urban Data Science Project – 60 credits

Over the summer months you'll 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'll 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
• Pollution
• Vulnerable populations
• Geodemographics
• Fieldwork

Optional modules

Please note: The modules listed below are indicative of typical options.

Geographic Data Visualisation & Analysis – 15 credits

Develop core visualisation and spatial analysis and statistical skills required for the analysis of geographically referenced data. You are introduced to ‘traditional’ and ‘novel’ datasets at different spatial scales and granularities related to areas, individuals, households and neighborhoods.

Geodemographics and Neighbourhood Analysis – 15 credits

You'll learn how area (neighbourhood) characteristics impact policy decisions in various organisations. You'll gain skills to construct and apply area measures for careers in academic, public, private, and third-sector settings. The module aims to help you analyse and utilise area characteristics to support decision-making in local planning, policy evaluation, and marketing.

Transport Data Collection and Analysis – 15 credits

Build skills and knowledge in the fundamentals of data collection and analysis in the context of transport. This module addresses the loop covering research questions, data requirements, data collection/generation, data analysis, and interpretation.

Transport Data Science – 15 credits

Develop an understanding of how your knowledge in data science can support sustainable transport policies using new techniques and datasets, ranging from openly available origin-destination datasets to huge datasets from global positioning systems (GPS). Not only does this module teach you data skills, but it also teaches you the importance of understanding how advanced data analysis, modelling and visualisation can support the global transition away from fossil fuels.

Fieldwork

Field courses provide students an opportunity to explore urban analytics ‘on the ground’ in inspiring urban environments. Students will consider cities from different perspectives and observe urban systems evolve across traditional policy areas. There will be a chance to get involved in collecting data, making observations and assessments, and explore cities in ways you have never done before.

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'll work with other students in teams to tackle problems and datasets provided by external stakeholders. Within this module, you'll 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.

Active research environment

You'll 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.

Specialist facilities

You'll 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.

Programme team

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

Entry requirements

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.

All applicants must have an interest in learning how to apply data science to tackle real-life urban challenges.

Applicants with any of the following will be considered on a case-by-case basis:

• Several years of professional experience in a relevant field where applicants do not meet the above requirement. In this case, please contact the Admissions Team to discuss your suitability for the programme.

International

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). 

We also offer online pre-sessionals alongside our on-campus pre-sessionals. Find out more about our six week online pre-sessional.

You can also study pre-sessionals for longer periods – read about our postgraduate pre-sessional English courses.

How to apply

Application deadlines

Please note: applications for this course open on the 1^st October 2024.

Applicants are encouraged to apply as early as possible.

30 June 2025 – International applicants

12 September 2025 – UK applicants

If you're still 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.

Admissions policy

University of Leeds Admissions Policy 2025

This course is taught by

School of Geography
School of Computer Science
Institute for Transport Studies

Contact us

School of Geography Postgraduate Admissions Team

Email: geo-tpg-enq@leeds.ac.uk
Telephone:

Fees

UK: £14,250 (Total)

International: £32,750 (Total)

Read more about paying fees and charges.

For fees information for international taught postgraduate students, read Masters fees.

Additional cost information

Travel and accommodation costs associated with compulsory field trips are covered by the university. However, you must pay for subsistence, incidental or personal expenses.

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 on our living costs and budgeting page.

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

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'll 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, University of Leeds students are among the top 5 most targeted by top employers according to The Graduate Market 2024, High Fliers Research, meaning our graduates are highly sought after by some of the most reputable companies in the field.

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

Careers support

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 Careers Service 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 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 careers fairs and industry talks in specialist areas and across broader industries, with employers who are actively recruiting for roles, giving you the opportunity to network and engage with industry sponsors. 
• Employability skills training – to support your transition to the workplace, we embed training in a range of key transferable skills valued by employers such as research and data analysis in all our programmes.
• 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.