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Urban Spatial Science Degree Apprenticeship MSc

London, Bloomsbury

The Urban Spatial Science Degree Apprenticeship MSc equips students with a multidisciplinary, critical lens for analysing and shaping global urban resilience and sustainability. You’ll gain expertise in data analytics, machine learning (ML), remote sensing, and reproducible research - tools essential for understanding, monitoring and improving cities around the world. 

UK students International students
Study mode
Flexible
UK tuition fees (2026/27)
See Fees Note
Programme also available on a modular (flexible) basis.
Overseas tuition fees (2026/27)
See Fees Note
Programme also available on a modular (flexible) basis.
Duration
Not applicable
3 academic years
Programme starts
September 2026
Applications accepted
Applicants who don't require a visa: 20 Oct 2025 – 21 Aug 2026
Applications close at 5pm UK time

Applications open

Apply for this course

Entry requirements

Candidates must have a sponsoring employer based in England who will employ them in a spatial data science or geographic information science role and is prepared to provide a work place mentor and enter into an employer agreement with UCL. Applicants who do not have this arrangement may be interested in applying for the Urban Spatial Science MSc instead.

A minimum of a lower second-class Bachelor’s degree in a relevant subject from a UK university or an overseas qualification of an equivalent standard.

The English language level for this course is: Level 1

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 Urban Spatial Science MSc delves into the theoretical, social, and scientific underpinnings of the modern built environment through a geospatial, data-centric approach. 

This Master's course emphasises a hands-on understanding of advanced technical and methodological practices in urban analytics and data-driven decision-making. You will gain expertise in mathematical, statistical, and simulation modelling; computer programming; spatial analysis; and data visualisation. These practical skills are reinforced by broad theoretical perspectives covering demographics, economics, urban form and function, network interactions and complexity, governance and policy, planning, and urban science. 

The Degree Apprenticeship (DA) route allows an Apprentice to study for a degree in Urban Spatial Science MSc, while continuing with employment. The degree is made up of eight taught modules, one research module and an End Point Assessment (EPA) totalling 180 credits.

The Apprentice will study at UCL for one day per week and work for their employer for the remaining four days. The Apprentice must be provided with relevant learning opportunities by the employer.

The course will be delivered part-time, with all 180 credits being studied in Years 1 and 2. The employer must agree for the Apprentice to progress to the EPA, expected in Year 3.

This route has been designed to ensure teaching is provided on one day each week during term time. Students who wish to select alternative additional taught modules to those suggested by the Course Leader, may do so only with their employer’s permission and with the approval of the Course Leader.

Who this course is for

We are looking for students interested in cities, environment, spatial science and computational methods. There is no required academic background, but those students with architecture, planning or geography degrees would be suited to the course. We welcome applicants from any stage of their career. 

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

What this course will give you

In-demand skills: Through our influential research and extensive collaboration with industry, we have developed a curriculum that will provide you with highly sought after skills and knowledge. Students will learn to perform reproducible and data-informed urban analytics using programming languages and development tools such as R, Python, SQL, Google Earth Engine, Git/GitHub and Docker/Podman, as well as new GenAI tools, underpinned by broad-based and critical theoretical perspectives on planning and city science.

Innovative teaching: We employ a wide mix of teaching and assessment formats, allowing students to develop and demonstrate learning beyond the lecture and essay. 
 
Access to a ‘World leading’ research environment: The Bartlett Centre for Advanced Spatial Analysis (CASA) is a renowned research centre in the science of cities; generating new knowledge and insights for use in city planning, policy and design; and drawing on the latest geospatial methods and ideas in computer-based visualisation and modelling. It is part of The Bartlett, UCL's Faculty of the Built Environment, where 91% of research was deemed ‘World Leading’ and ‘Internationally Excellent’ in the latest Research Excellence Framework (REF 2021). The Bartlett was also ranked #1 for Research Power in the built environment.  
 
Top ranked education: For the third year in a row, The Bartlett Faculty of the Built Environment was ranked #1 in the world for ‘Architecture and Built Environment’ (QS World University Subject Rankings 2025). 
 
Career support: Studying at CASA provides students with access to a range of career services including networking events, career workshops, and internship opportunities. Our graduates go on to a range of highly skilled jobs in industry, government, and the Third sector. Destinations for graduates include Foster and Partners, Huawei Technologies, Siemens, Urban Redevelopment Authority (Singapore), and Transport for London. 

Social and networking opportunities: The department supports students in networking with staff, graduates, and fellow students through an active course of lectures and social events as well as an active alumni mailing list.

Find out more about the benefits of studying at the Centre for Advanced Spatial Analysis. 

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

The foundation of your career

97.2% of The Centre for Advanced Spatial Analysis graduates were in work or further study 15 months after graduation (Graduate Outcomes Surveys 2017-22).

Top industry sectors for The Centre for Advanced Spatial Analysis graduates in work are IT, technology and telecommunications (24.1% of graduates); construction, built environment and property (13.9%); manufacturing (8.9%); accountancy and financial services (7.6%); and academic research and HE (7.6%)

The Centre for Advanced Spatial Analysis graduates are working in 17 countries around the world.

Example employers:

  • ARUP
  • UCL
  • Accenture plc
  • WSP Group
  • 3D Repo
  • Westminster Council
  • Ordnance Survey
  • CACI
  • Geolytix
  • Uber 

Employability

This course provides students with the technical skills and knowledge base to embark on a professional or academic path through the highly interdisciplinary field of urban spatial science and the wider urban planning and policy fields. Graduates from our department have gone on to pursue a wide variety of careers in local government, urban planning, software development and academic research (Graduate Outcomes Surveys 2017-22). 

Networking

A regular series of seminars given by guest lecturers provides students with an opportunity to learn form, and network with, academics and professionals from UCL and other prestigious organisations.

Additionally, students gain access to our extensive alumni network of professionals via our careers and alumni events.

Teaching and learning

The modules on the course are delivered through a combination of diverse teaching and learning activities in traditional and ‘flipped’ formats. Lectures feature widely, as do computer-based practical classes, tutorials alongside both student and teacher led discussion groups. Self-study is expected throughout the programme. In addition to formal teaching, students can learn directly from experts in the built environment and spatial analysis through the weekly term time CASA seminar series.

Assessment is undertaken via a variety of means, including practical projects, group presentations, exams, portfolios, visualisations, written technical coursework reports, essays, and a final research dissertation. 

The Apprentice will study at UCL for one day per week and work for their employer for the remaining four days. The Apprentice must be provided with relevant learning opportunities by the employer.

Modules

The course will be delivered part-time, with all 180 credits being studied in Years 1 and 2. 

The employer must agree for the Apprentice to progress to the EPA, expected in Year 3. 

Compulsory Taught Modules (60 credits) 

  • CASA0001 Urban Systems theory (15 credits) 
  • CASA0005 Geographic Information Systems and Science (15 credits) 
  • CASA0007 Quantitative Methods (15 credits) 
  • CASA0013 Foundations of Spatial Data Science (15 credits) 

Compulsory Research Modules (60 credits) 

  • CASA0010 Dissertation (60 credits) 

Additional Taught Modules (60 credits)* 

  • CASA0006 Data Science for Spatial Systems (15 credits) 
  • CASA0008 Smart Cities: Context, Policy and Government (15 credits) 
  • CASA0023 Remote Sensing Cities and Environments (15 credits) 
  • CASA0025 Building Spatial Applications with Big Data (15 credits) 

*This route has been designed to ensure teaching is provided on one day each week during term time. Students who wish to select alternative additional taught modules to those listed, may do so only with their employer’s permission and with the approval of the Module Leader.

Year 1

  • CASA0005 Geographic Information Systems and Science 
  • CASA0013 Foundations of Spatial Date Science 
  • CASA0023 Remote Sensing Cities and Environments 
  • CASA0025 Building Spatial Applications with Big Data 
  • CASA0010 Dissertation 

Year 2

  • CASA0001 Urban Systems theory 
  • CASA0007 Quantitative Methods 
  • CASA0006 Data Science for Spatial Systems 
  • CASA0008 Smart Cities: Context, Policy and Government 
  • CASA0010 Dissertation 

Year 3

  • End Point Assessment (EPA)

Compulsory modules








Optional modules


Group Mini Project: Digital Visualisation





PropTech: Introduction



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.

Placement

As part of the dissertation module students may have opportunities to collaboratively work with external organisations on dissertation projects. This usually involves meeting in the partner’s office (the academic supervisor is typically present as well), but on occasion students may be allocated a workspace. However, this is not a requirement of any dissertation project or the module and is on a case-by-case basis.

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: The Bartlett Centre for Advanced Spatial Analysis

Join our virtual event to explore our postgraduate courses, hear from academic staff and current students, and learn about the application process, scholarships, and career support. A live Q&A will give you the chance to get your questions answered. Take the next step toward shaping a more sustainable built environment with us.

Watch on demand event

Online - Open day

Graduate Open Events: Bartlett Promise UK Scholarship

Join our virtual event to explore our postgraduate courses, hear from academic staff and current students, and learn about the application process, scholarships, and career support. A live Q&A will give you the chance to get your questions answered. Take the next step toward shaping a more sustainable built environment with us.

Watch on demand event

Fees and funding

Fees for this course

UK students International students
Fee description Full-time
Tuition fees (2026/27) See Fees Note
Tuition fees (2026/27) See Fees Note

Programme also available on a modular (flexible) basis.

Additional costs

A standard specification laptop, with at least 32GB of RAM and a minimum of 50GB of free disk space is strongly recommended. Approximately £800-£2000.

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

The fees for the Degree Apprenticeship are paid by the Apprentice's employer, via the apprenticeship levy.

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

Bartlett Promise Sub-Saharan Africa Masters Scholarship

Deadline: 29 March 2026
Value: Fees, stipend and other allowances (Duration of programme)
Criteria Based on financial need
Eligibility: Overseas

Bartlett Promise UK Master's Scholarship

Deadline: 31 May 2026
Value: Full tuition fees and an annual stipend of £17,096 for a 12 month master's or £15,864 for a 9 month (Duration of programme)
Criteria Based on financial need
Eligibility: UK

UCL East London Scholarship

Deadline: 25 June 2026
Value: Tuition fees plus £17,096 stipend ()
Criteria Based on financial need
Eligibility: UK

Next steps

When we assess your application we would like to learn:

  • why you want to study Urban Spatial Science at graduate level
  • why you want to study Urban Spatial Science at UCL
  • what particularly attracts you to this course
  • how your academic and professional background meets the demands of this course
  • where you would like to go professionally with your degree

Together with essential academic requirements, the personal statement is your opportunity to illustrate whether your reasons for applying to this course match what the programme will deliver.

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.

Apply for this course

Got questions? Get in touch

Centre for Advanced Spatial Analysis
Centre for Advanced Spatial Analysis

bartlett.pg-casa@ucl.ac.uk

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