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.
If your education has not been conducted in the English language, you will be expected to demonstrate evidence of an adequate level of English proficiency.
The English language level for this programme is: Standard.
Further information can be found on our English language requirements page.
Months of entry
With the rapid development of smart sensors, smartphones and social media, "big" data is ubiquitous. This new MSc teaches the foundations of GIScience, database, spatial analysis, data mining and analytics to equip professionals with the tools and techniques to analyse, represent and model large and complex spatio-temporal datasets.
As one of the world\'s top universities, UCL excels across the physical and engineering sciences, social sciences and humanities.
Spanning two UCL faculties, this interdisciplinary programme exploits the complementary research interests and teaching programmes of three departments (Civil, Environmental and Geomatic Engineering, Computer Science, and Geography).
Students on the Spatio-Temporal Analytics and Big Data Mining programme will be part of a vibrant, enthusiastic, and international research environment in which collaboration and free-ranging debate are strongly encouraged. This is supported by weekly research seminars and industrial seminars from top employers in the field.
Full-time: 1 year;
Fees and funding
Fee UK/EU Full-time: GBP11,800; Overseas Full-time: GBP24,610;
Qualification and course duration
The programme is delivered through a combination of lectures, seminars, and laboratory practicals. Assessment is through examination, coursework, practicals, dissertation, and poster presentation.
Course contact details
- +44 (0)20 3370 1214