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.
Students will be equipped with computational foundations and skills needed for big data analytics including visualisation, prediction, clustering and simulation with statistical and machine learning approaches, as well as retrieving and mining big (open) data, web services and cloud computing, web and mobile applications, by practising with real case data and open software.
Students undertake modules to the value of 180 credits.
The programme consists of four core modules (60 credits), four optional modules (60 credits) and a dissertation/report (60 credits).
A Postgraduate Diploma, four core modules (60 credits), two optional modules (60 credits), full-time nine months is offered.
Core modules -GIS Principles and Technology -Principles of Spatial Analysis -Spatial Databases and Data Management -Spatio-temporal Analysis and Data Mining
Choose four options from the following: -Introductory Programming (requires Applied Machine Learning option) -Complex Networks and Web -Representation, Structures and Algorithms -Mapping Science -Supervised Learning (requires Applied Machine Learning) -Web Mobile GIS -Information Retrieval & Data Mining (requires Introductory Programming) -Geographic Information System Design -Applied Machine Learning (requires Introductory Programming, and Supervised Learning)
Dissertation/report All students undertake an independent research project which culminates in a dissertation of 15,000 words.
Teaching and learning The programme is delivered through a combination of lectures, seminars, and laboratory practicals. Assessment is through examination, coursework, practicals, dissertation, and poster presentation.
Graduates from this programme are expected to find positions in consultancy, local government, public industry, and the information supply industry, as well as in continued research. Possible career paths could include: data scientist in the social media, finance, health, telecoms, retail or construction and planning industries; developer of spatial tools and specialised spatial software; researcher or entrepreneur.
Why study this degree at UCL?
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 & 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.