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Social and Geographic Data Science MSc

London, Bloomsbury

With growing demand for experts who can interpret spatial and social data, this course equips students with the analytical and technical skills to thrive in social and geographical data science. You’ll study at the intersection of computing, spatial statistics, machine learning, GeoAI and the social sciences, tackling challenges in domains such as urban planning, mobility, public health, and environmental management. You’ll work with leading researchers at UCL and benefit from links to institutions such as the Consumer Data Research Centre and the Alan Turing Institute. This course prepares you for data-driven careers in government, industry, research, and NGOs.

UK students International students
Study mode
UK tuition fees (2026/27)
£16,800
£8,400
Overseas tuition fees (2026/27)
£35,400
£17,700
Duration
1 calendar year
2 calendar years
Programme starts
September 2026
Applications accepted
Applicants who require a visa: 20 Oct 2025 – 26 Jun 2026
Applications close at 5pm UK time

Applications open

Applicants who do not require a visa: 20 Oct 2025 – 28 Aug 2026
Applications close at 5pm UK time

Applications open

Apply for this course

Entry requirements

Normally a minimum of an upper second-class Bachelor's degree in a relevant discipline from a UK university or an overseas qualification of an equivalent standard.

The English language level for this course is: Level 4

UCL Pre-Master's and Pre-sessional English courses are for international students who are aiming to study for a postgraduate degree at UCL. The courses will develop your academic English and academic skills required to succeed at postgraduate level.

Further information can be found on our English language requirements page.

Equivalent qualifications

Country-specific information, including details of when UCL representatives are visiting your part of the world, can be obtained from the International Students website.

International applicants can find out the equivalent qualification for their country by selecting from the list below. Please note that the equivalency will correspond to the broad UK degree classification stated on this page (e.g. upper second-class). Where a specific overall percentage is required in the UK qualification, the international equivalency will be higher than that stated below. Please contact Graduate Admissions should you require further advice.

About this degree


The programme aims to give you a rigorous training in the tools and theories that underpin modern data science, with a focus on spatial and social applications in areas such as urban planning, transport, public health, and environmental management. You will gain core expertise in geographic information systems (GIS), spatial analysis, statistical learning, GeoAI, data storytelling and computational social science, with the flexibility to explore advanced topics such as cartography, remote sensing, citizen science, causal inference and urban analytics. 

The programme equips graduates with the critical, technical, and analytical skills needed to understand and address real-world challenges using spatial and social data, and to navigate the ethical and policy contexts in which data science operates.

Who this course is for

This programme is ideal for students with a quantitative background in social science who are interested in developing advanced skills in data analysis and geographic information science. It will also appeal to professionals with experience in data science, GIS, social data science or computing seeking to enhance their expertise.

Read about what it takes to study for a Master's at UCL

What this course will give you

This MSc offers a distinctive opportunity to develop expertise at the forefront of data science applied to social and geographic challenges. You will benefit from:

  • a dynamic, collaborative learning environment, where leading researchers actively contribute to teaching, ensuring you engage with cutting-edge advances in data science, spatial analysis, and social science methods
  • a course designed to nurture intellectual curiosity and practical skills, equipping you to address complex, real-world challenges in areas such as urban planning, mobility, public health and environmental management - using advanced social data science techniques such as spatial statistics, and GeoAI, geographic information systems (GIS), data storytelling and computational social science
  • exceptional flexibility to tailor your degree, choosing from a wide range of specialist modules including spatial statistics, data visualisation, and computational methods aligned with your personal interests and career goals
  • access to outstanding resources and networks, anchored by UCL’s central London location—at the heart of a global hub for data innovation, with proximity to world-leading institutions
  • a vibrant, international academic community, fostering collaboration with scholars and practitioners worldwide, and preparing you for careers across academia, government, NGOs, and industry sectors where expertise in spatial and social data science is increasingly sought after
  • comprehensive development of analytical, technical, and communication skills, enhancing your employability in diverse fields including technology, urban planning, environmental management, and public policy.

Graduates leave the course well-equipped to contribute effectively to the evolving landscape of data-driven decision-making, research, and innovation.

"The Department’s comprehensive approach to learning and its focus on real-world applications make it an ideal choice for anyone aspiring to excel in this dynamic and evolving field." — Wanxin Yang, UCL Department of Geography graduate

Read about what you'll get out of a graduate programme

The foundation of your career

Graduates of the MSc Social and Geographic Data Science are well equipped for careers at the intersection of spatial analysis, social science, data science, and policy. The course develops highly sought-after skills in computational social science, geospatial data wrangling and analysis, spatial statistics, machine learning, urban analytics, GeoAI and social research methods—skills that are increasingly valued across academia, industry, government, and the third sector.

Alumni have secured roles in organisations such as The Alan Turing Institute, Transport for London, ARUP, UK local councils, the Organisation for Economic Co-operation and Development (OECD), GHD Movement Strategies. They have also continued their doctoral studies at universities in the UK, US or Asia, working on projects ranging from urban analytics, GeoAI and mobility modelling to international development and open data infrastructure (Graduate Outcomes survey 2017–2022).

Many graduates go on to employment in research organisations, consultancies, and government departments, while others pursue further academic study. The course also provides an excellent foundation for PhD research in quantitative social science, spatial analysis, and data-driven public policy.

Employability

This programme meets growing demand for data scientists who can integrate advanced technical skills with a critical understanding of social and geographic issues. Its interdisciplinary approach provides a unique foundation for applying data science in real-world, socially relevant contexts.

You will develop expertise in:

  • data analysis, modelling and visualisation using modern statistical and computational tools
  • geographic Information Systems (GIS) and spatial data interpretation
  • quantitative research design and evidence-based reasoning
  • applying data science methods to pressing socio-economic and urban challenges in areas such as urban planning, transport, public health, and environmental management
  • learning advanced data science techniques such as spatial statistics, causal inference, data storytelling and GeoAI or Deep Learning applied in Geography.

In addition, the programme fosters a range of transferable skills valued across sectors:

  • critical thinking and problem solving
  • effective communication of complex findings to diverse audiences
  • interdisciplinary collaboration
  • project planning and independent research.

These attributes equip you to work confidently at the intersection of data, society and space—preparing you for roles in government, academia, private industry, or further research.

Networking

Students benefit from the expertise of world-leading researchers in spatial analysis, data science, and geographic information systems. The interdisciplinary structure of the course offers the opportunity to build knowledge across diverse subject areas, engaging with academics from the Department of Geography and the wider UCL community.

The Department hosts annual careers events where alumni share insights into their post-graduation pathways, including roles in data science, public policy, research, and consultancy. These events, alongside UCL’s wider careers provision and student networks, offer valuable opportunities to connect with professionals, explore career trajectories, and grow your professional network in data-driven sectors.

Teaching and learning

The course is delivered through a combination of lectures, seminars, tutorials, and computer-based practical classes. These diverse teaching methods provide a strong foundation in both theoretical knowledge and practical skills relevant to social and geographic data science. Practical classes include group work and individual oral presentations designed to develop communication and teamwork skills.

Throughout the course, interactive sessions foster critical engagement with data analysis, spatial modelling, and computational techniques. Supportive tutorials and workshops enhance students’ ability to apply quantitative and qualitative methods to real-world research questions.

This varied approach to teaching and learning is designed to ensure students achieve the course’s learning outcomes by equipping them with the technical expertise, analytical thinking, and interdisciplinary understanding needed to tackle complex social and geographic data challenges.

Assessment on this programme is designed to support your development of key analytical and technical skills in data science and spatial analysis. You will be assessed through a combination of a combination of individual coursework including a mix of research-led topics, applications reports and essays, report and oral presentation-based group coursework, posters and a 12,000 word research dissertation.

These assessment methods are intended to reflect the programme’s emphasis on applied quantitative methods, enabling you to demonstrate your ability to work with data, conduct spatial analysis, and communicate results to diverse audiences.

For full-time students, contact time typically amounts to around 12 hours per week. Outside of lectures, seminars, workshops, and tutorials, full-time students use their remaining time for self-directed study and completing coursework assignments (approximately 20-25 hours).

Additionally, you will be expected to complete a dissertation worth up to 60 credits, with regular guidance and support from your supervisor throughout.

A Postgraduate Diploma (120 credits, full-time nine months, part-time two years) is offered. A Postgraduate Certificate (60 credits, full-time 12 weeks, part-time one year) is offered.

Modules

As a full-time student, you will complete eight taught modules—four compulsory and four optional—as well as a research dissertation.

Term 1:
You will be introduced to the theoretical foundations and key concepts in social and geographic data science, including critical engagement with the political and societal implications of data. You will typically take the core modules Principles of Spatial Analysis (GEOG0114), Introduction to Social Data Science (GEOG0115), and Data, Politics and Society (GEOG0163) and one other optional module.

Term 2:
You will explore more advanced techniques in data science and data mining, with a focus on applications to geographical and socio-economic challenges. You will continue your taught modules, selecting from a range of optional topics to complement your core learning. You will take the GEOG0125 Advanced Topics in Social and Geographic Data Science core module and three other optional modules. 

Term 3 and Summer:
You will complete a research dissertation in an area relevant to social and geographic data science. Research and writing take place during Term 3 and the summer, culminating in submission at the end of the academic year.

Teaching takes place across Terms 1 and 2. As a part-time student, you will undertake eight taught modules over two academic years and complete a research dissertation. Modules are delivered through lectures, seminars, and computer-based practicals.

Part-time students discuss their individual pathway through the course with the Course Convenor. We aim to be flexible in supporting your route through the degree.

Year 1
Term 1: You will typically take the core modules Principles of Spatial Analysis (GEOG0114) and Introduction to Social Data Science (GEOG0115), which serve as prerequisites for several later modules.
Term 2: You may begin taking optional modules depending on your chosen pathway.

Year 2
Term 1: You will take the core modules of Advanced Topics in Social and Geographic Data Science (GEOG0125) and Data, Politics and Society (GEOG0163).
Term 2: You will complete any remaining optional modules.
Term 3 and Summer: You will undertake and complete your dissertation.

As a modular flexible student, you can engage with the programme at your own pace over a maximum of five years, completing the required four core modules and four optional modules within that period. The core modules introduce key concepts in social data science, spatial analysis, and the societal context of data. 

You are encouraged to plan your module choices in consultation with the Course Convenor to suit your academic and professional interests. Students may select up to two optional modules from outside the Department, subject to approval. 

Suggested options include:

The course concludes with a research dissertation undertaken in Term Three, with independent work carried out over the summer period.

Compulsory modules







Optional modules













Please note that the list of modules given here is indicative. This information is published a long time in advance of enrolment and module content and availability are subject to change. Modules that are in use for the current academic year are linked for further information. Where no link is present, further information is not yet available.

Students undertake modules to the value of 180 credits. Upon successful completion of 180 credits, you will be awarded an MSc in Social and Geographic Data Science. Upon successful completion of 120 credits, you will be awarded a PG Dip in Social and Geographic Data Science. Upon successful completion of 60 credits, you will be awarded a PG Cert in Social and Geographic Data Science.

Placement

Students on this course have the opportunity to undertake dissertation research in collaboration with a range of external partners across sectors, including commercial organisations, NGOs, and local government bodies.

Over the past five years, students have participated in the Master’s Dissertation Scheme run by the Consumer Data Research Centre (CDRC), based at UCL Geography. This scheme facilitates applied research with high-profile partners such as Arup, Green Street, West Midlands Transport Authority, Geolytix, Nokia Bell Labs, Tesco, and GHD Movement Strategies.

These collaborations offer valuable experience working with real-world data and applying advanced spatial and data science methods in professional settings.

For more details, please visit the CDRC Master’s Dissertation Scheme.

Accessibility

The department will endeavour to make reasonable adjustments for students with disabilities, including those with long-term health conditions, neurodivergence, learning differences and mental health conditions. This list is not exhaustive. If you're unsure of your eligibility for reasonable adjustments at UCL, please contact Student Support and Wellbeing Services.

Reasonable adjustments are implemented on a case-by-case basis. With the student's consent, reasonable adjustments are considered by UCL Student Support and Wellbeing Services, and where required, in collaboration with the respective department.

Details of the accessibility of UCL buildings can be obtained from AccessAble. Further information about support available can be obtained from UCL Student Support and Wellbeing Services.

For more information about the department and accessibility arrangements for your course, please contact the department.

Visit us

All open days and events

Online - Open day

Graduate Open Events: PGT study at UCL Geography (AM)

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Discover what makes us a world-leading centre for geographical research and postgraduate taught study. Whether you are interested in studying climate change or nature conservation, human migration or urban studies, or acquiring new skills from environmental modelling to social data science, our research-led programmes can help you unlock this next step. Meet our Postgraduate Programme Director, Dr Sam Randalls and Deputy Director, Prof Jon French and current MSc students.

Online - Open day

Graduate Open Events: PGT study at UCL Geography (PM)

—

Discover what makes us a world-leading centre for geographical research and postgraduate taught study. Whether you are interested in studying climate change or nature conservation, human migration or urban studies, or acquiring new skills from environmental modelling to social data science, our research-led programmes can help you unlock this next step. Meet our Postgraduate Programme Director, Dr Sam Randalls and Deputy Director, Prof Jon French and current MSc students.

Fees and funding

Fees for this course

UK students International students
Fee description Full-time Part-time
Tuition fees (2026/27) £16,800 £8,400
Tuition fees (2026/27) £35,400 £17,700

Postgraduate Taught students benefit from a cohort guarantee, meaning that their tuition fees will not increase during the course of the programme, but UCL reserves the right to increase tuition fees to reflect any sums (including levies, taxes, or similar financial charges) that UCL is required to pay any governmental authority in connection with tuition fees.

The tuition fees shown are for the year indicated above. Where the course is offered on a flexible/modular basis, fees are charged pro-rata to the appropriate full-time Master's fee taken in an academic session. Further information on fee status, fee increases and the fee schedule can be viewed on the UCL Students website: ucl.ac.uk/students/fees.

Additional costs

For full-time and part-time offer holders with a fee status classification of UK, a fee deposit will be charged at 2.5% of the first year fee.

For full-time and part-time offer holders with a fee status classification of Overseas, a fee deposit will be charged at 10% of the first year fee.

There is no fee deposit required for PG Dip and PG Cert applicants.

Further information can be found in the Tuition fee deposits section on this page: Tuition fees.

Students will produce a poster for the final dissertation presentation, which incur printing costs of approximately £20, depending on format and provider. Templates are provided to allow for printing on standard A4 or A3 paper, though many students choose to print in A0 format using UCL's printing services.

There are no additional costs for placements.

For in-person teaching, UCL’s main teaching locations are in zones 1 (Bloomsbury) and zones 2/3 (UCL East). The cost of a monthly 18+ Oyster travel card for zones 1-2 is £119.90. This price was published by TfL in 2025. For more information on additional costs for prospective students and the cost of living in London, please view our estimated cost of essential expenditure at UCL's cost of living guide.

Funding your studies

Information about funding opportunities for the MSc Social and Geographic Data Science course can be found via UCL’s Scholarships Finder. Applicants are encouraged to explore a wide range of scholarships, studentships, and bursaries available to support their studies.

For a comprehensive list of the funding opportunities available at UCL, including funding relevant to your nationality, please visit the Scholarships and Funding website.

See all the ways you can fund your studies

Aziz Foundation Scholarships in Social and Historical Sciences

Value: Full tuition fees (equivalent to 1yr full-time) (1 year)
Criteria Based on financial need
Eligibility: UK

Next steps

There is an application processing fee for this course of £90 for online applications. Further information can be found at Application fees.

When we assess your application, we would like to learn:

  • why you want to study Social and Geographic Data Science
  • why you want to study Social and Geographic Data Science at UCL
  • what particularly attracts you to this course
  • how your academic and/or professional background prepares you for the challenges of this rigorous and quantitative field
  • where you would like to go professionally with your degree.

Together with meeting essential academic requirements, your personal statement is your opportunity to demonstrate how your motivations align with what the course offers, and to showcase your suitability and experience.

Please note that you may submit applications for a maximum of two graduate courses (or one application for the Law LLM) in any application cycle.

Choose your programme

Please read the Application Guidance before proceeding with your application.

Year of entry: 2026-2027

Apply for this course

Got questions? Get in touch

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Geography

geog.office@ucl.ac.uk

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