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Spatio-temporal Analytics and Big Data Mining MSc

London, Bloomsbury

This is the programme information for 2026/27 entry

If you require details of the previous year's programme, Spatio-temporal Analytics and Big Data Mining MSc (2025/26), click here

UK students International students

Study mode

UK tuition fees (2026/27)

£21,500

£10,750

Overseas tuition fees (2026/27)

£42,700

£21,350

Duration

1 calendar year

2 calendar years

Programme starts

September 2026

Applications accepted

Applicants who require a visa: 20 Oct 2025 – 27 Mar 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

A minimum of an upper second-class UK Bachelor's degree in a relevant discipline (such as engineering, mathematics, computer science, environmental science, human or physical geography, geology, forestry, oceanography, or physics) or an overseas qualification of an equivalent standard. Applicants with relevant professional experience are also considered.

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

This specialist MSc will train you to extract insights from large amounts of data to discover patterns and knowledge from spatio-temporal data.

Teaching combines theory with extensive hands-on experience to cover the diverse facets of big data – from the principles of spatio-temporal analysis and computation guided by statistical and machine learning techniques, to space time data, parallel computing, system design, social media analysis, text mining, and programming.

You'll apply your skills to real-world scenarios, to create models for social media listening, understand weather patterns, predict earthquakes, and determine global warming trends.

You’ll also learn all about the ethical and social angles to big data that are needed in the working world. This “Bigger Picture” element will help you understand the context of your work, so you can go out and create and deliver projects that benefit both people and the planet.

On top of learning practical skills from programming languages (R and Python) and scientific writing, there’s a big emphasis on developing transferable skills.

These include communication, project management, and critical thinking – which, when coupled with your tech expertise, will make you highly sought after for roles in industries including data science, social media analysis, finance, health, telecoms, and urban planning.

Who this course is for

This programme is ideal if you want to elevate your expertise in big data to advance in a fulfilling career, or go on to further research.

We welcome applications from recent graduates in engineering, architecture, physical or computational sciences, mathematics, earth sciences, physics or related fields, and from those with recent professional experience.

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

What this course will give you

This programme offers you the following benefits and opportunities.

A postgraduate degree from a top-ranked university. UCL is consistently ranked among the best universities globally (ranked 9th in the latest QS World University Rankings 2026), providing you with a prestigious qualification that is highly regarded by employers worldwide.
Study alongside expert academics and researchers in data science, cybercrime, computation, infrastructure, geospatial sciences, urban simulation, machine learning, and more.
Build a successful career in big data, supported by our close industry and research links. You'll access exclusive seminars and exhibitions with industry leaders at UCL.
Gain hands-on experience with various data acquisition tools, software, programming languages (R and Python), real-case data, and open-source software.
UCL’s Bloomsbury campus is in the heart of a London district famous for its cultural and educational institutions.

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

The foundation of your career

Graduates from the programme have gone on to work with employers such as UBS Investment Bank, Panasonic, Datacup, and Wegaw, whilst others go on to research positions in world-leading academic institutions, such as the University of Cambridge and Universidad del Azuay (Graduate Outcomes Survey 2017-22).

Employability

Our programme offers a combination of theory, practice, and innovation that will give you the strong technical and contextual foundation you need to progress into a big data career in industry, or to conduct further research.

Networking

You’ll have regular opportunities to connect, collaborate and build professional contacts as part of your Master’s.

Engage with peers, industry experts and faculty members at guest lectures and special seminars.
Take part in collaborative group projects, field trips, site visits, case studies, and workshops within the department and with industry partners.
Access UCL Careers for a variety of resources and events to support your career development, including CV workshops and 1-2-1 guidance.

Teaching and learning

This MSc programme is delivered through a mix of seminars, lectures, laboratory work, projects and practicals. These frequently draw upon real-life industry case studies with ample opportunities to gain hands-on experience.

Assessment is through examinations (short-answer and multiple-choice questions), presentations, essays, coursework, and your research project, which you will submit as a dissertation.

Full-time students can expect 12-16 hours of contact time per teaching week. Outside these sessions, students are expected to engage in significant self-directed study and complete assessments of around 20-25 hours per week. The exact number of contact hours, composition, and assessment varies throughout the terms, and depends on the module choices of the student.

This is a full-time course, which means students should expect a working schedule of approximately 35-40 hours a week.

A Postgraduate Diploma, consisting of five core modules (75 credits) and three optional modules (45 credits), taken full-time over nine months is also offered.

Modules

The programme structure for full-time students encompasses a total of 180 credits. The programme consists of 3 compulsory modules, 5 optional modules and a dissertation/report.

The programme structure for part-time students encompasses a total of 180 credits over the course of 2 years.

The programme consists of 3 compulsory modules, 5 optional modules and a dissertation/report.

The programme structure for modular/flexible students encompasses a total of 180 credits over the course of their studies.

Compulsory modules

Machine Learning for Data Science

Spatial-Temporal Data Analysis and Data Mining (STDM)

Research Project

Geospatial Science

Geospatial Programming

Spatial Analysis and Geocomputation

Optional modules

Web and Mobile GIS - Apps and Programming

Spatial Databases and Data Management

Sensors and Location

Introduction to Complex Infrastructure Systems

Urban Simulation

Mining Social and Geographic Datasets

Cybercrime

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 Spatio-temporal Analytics and Big Data Mining. Upon successful completion of 120 credits, you will be awarded a PG Dip in Spatio-temporal Analytics and Big Data Mining.

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.

Fees and funding

Fees for this course

UK students International students

Fee description	Full-time	Part-time
Tuition fees (2026/27)	£21,500	£10,750
Tuition fees (2026/27)	£42,700	£21,350

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.

There are no additional costs associated with this programme.

For example, the costs associated with any possible site visits will be covered by the department.

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

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

: UCL East London Scholarship

CLOSED FOR 25/26 ENTRY

Value: Tuition fees plus £16,000 stipend ()

Criteria Based on financial need

Eligibility: UK

Next steps

Students are advised to apply as early as possible due to competition for places. Those applying for scholarship funding (particularly overseas applicants) should take note of application deadlines.

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 spatio-temporal analytics and big data mining at graduate level
why you want to study spatio-temporal analytics and big data mining at UCL
what particularly attracts you to this programme
how your academic and professional background meets the demands of this programme
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 programme 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.

This course requires two references. Further information regarding references can be found on this Selecting your references page.

Choose your programme

Please read the Application Guidance before proceeding with your application.