University College London (UCL)
Spatio-temporal Analytics and Big Data Mining MSc
London, United Kingdom
MSc
DURATION
1 year
LANGUAGES
English
PACE
Full time, Part time
APPLICATION DEADLINE
EARLIEST START DATE
Sep 2026
TUITION FEES
STUDY FORMAT
On-Campus
The MSc in Spatio-temporal Analytics and Big Data Mining offers students a chance to explore how to analyze large amounts of data that change over time and space. The course focuses on teaching methods and tools used to uncover patterns, trends, and insights from complex datasets. Students will learn to handle data from various sources, such as sensors, social media, and geographic information systems, all while developing skills to process and interpret big data effectively. The program combines practical skills with theoretical foundation, preparing students for roles that involve managing and analyzing massive, dynamic datasets.
Throughout the course, students will work on real-world problems and projects that require applying their knowledge to current challenges in industries like logistics, urban planning, and environmental monitoring. The curriculum emphasizes data mining, machine learning, and spatial analysis, giving students tools to make meaningful contributions to data-driven decision-making. By the end of the program, graduates will have built a robust set of skills suitable for careers in research, industry, or government agencies that rely on understanding spatio-temporal data for strategic planning and problem solving.
UCL Scholarships
There are a number of scholarships available to postgraduate students, including our UCL Masters Bursary for UK students and our UCL Global Masters Scholarship for international students. You can search via the scholarships finder for awards that you might be eligible for. Your academic department will also be able to provide you with more information about funding.
External Scholarships
Online aggregators like Postgraduate Studentships, Scholarship Search, Postgraduate Funding and International Financial Aid and College Scholarship Search contain information on a variety of external schemes.
If you have specific circumstances or ethnic or religious background it is worth searching for scholarships/bursaries/grants that relate to those things. Some schemes are very specific.
Funding for disabled students
Master's students who have a disability may be able to get extra funding for additional costs they incur to study.
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. 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
Full-time
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.
Part-time
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.
Flexible
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
Details of the accessibility of UCL buildings can be obtained from AccessAble. Further information can also be obtained from the UCL Student Support and Wellbeing Services team.
What this course will give you
- 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 2025), 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.
- Study in the world's best city for university students (QS Best Student Cities 2025). UCL’s Bloomsbury campus is in the heart of a London district famous for its cultural and educational institutions.
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.
Others go on to research positions in world-leading academic institutions, such as the University of Cambridge and Universidad del Azuay.
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.