Urban Data Science and Analytics MSc

Year of entry

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Start date
September 2024
Delivery type
On campus
Duration
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
£13,500 (Total)
International fees
£30,750 (Total)

Course overview

Image of students using the Data science helix computer cluster

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.

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 Computing.

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 (e.g. demographics, crime, health) and transport data analyses.

Project work

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

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

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.

Most courses consist of compulsory and optional modules. There may be some optional modules omitted below. This is because they are currently being refreshed to make sure students have the best possible experience. Before you enter each year, full details of all modules for that year will be provided.

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

Module Name Credits
Programming for Data Science 15
Data Science for Practical Applications 15
Creative Coding for Real World Problems 15
Analysing Cities 15
Analytics for Urban Policy 30
Urban Data Science Project 60

Year 1 optional modules (selection of typical options shown below)

Module Name Credits
Geographic Data Visualisation & Analysis 15
Geodemographics and Neighbourhood Analysis 15
Transport Data Collection and Analysis 15
Transport Data Science 15

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

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.

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.

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. 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

We operate a staged admissions process for this course with selection deadlines throughout the year.

Please read our How to Apply page for full details, including application deadlines and what to include with your application.

Click below to access the University’s online application system and find out more about the application process.

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 Taught Admissions Policy 2024

This course is taught by

School of Geography
School of Computing
Institute for Transport Studies

Contact us

School of Geography Postgraduate Admissions Team

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

Fees

UK: £13,500 (Total)

International: £30,750 (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 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.

Student profile: Jessica Arkesden

I decided that I needed to formally upskill to stay relevant in this changing market, and wanted to take advantage of the breadth and depth that a Masters degree could offer.
Find out more about Jessica Arkesden's time at Leeds