MSc Social and Geographic Data Science
Overview
There is ever-growing national and international demand for qualified professionals and scientists who have expertise in social and geographic data science. UCL's Social and Geographic Data Science MSc provides rigorous scientific and vocational training for the next generation of data scientists, with a unique expertise at the interface of social sciences, computing and statistics.
Structure
COMPULSORY MODULES (TERM ONE)
Module code | Module title | UCL Credit value |
---|---|---|
GEOG0125 | Advanced Topics in Social Data Science | 15 credits |
GEOG0114 | Principles of Spatial Analysis | 15 credits |
GEOG0115 | Introduction to Social Data Science |
15 credits |
GEOG0163 | Data, Politics and Society |
15 credits |
OPTIONAL MODULES (TERM TWO)
The four optional modules are normally selected from the following list, but not exclusively so. Due to sabbaticals and staff changes, not all modules are available every year, and module availability is subject to change. If you have questions relating to a specific optional module available in the forthcoming year, please contact the programme convenor.
Module code | Module title | UCL Credit value |
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CASA0005 | Geographic Information Systems and Science | 15 credits |
GEOG0051 | Mining Social and Geographic Datasets | 15 credits |
GEOG0149 | Urban Policy | 15 credits |
GEOG0152 | Introduction to Citizen Science & Scientific Crowdsourcing | 15 credits |
GEOG0162 | Cartography and Data Visualisation | 15 credits |
CASA0023 | Remotely Sensing Cities and Environments | 15 credits |
1 x 15 credit module may be taken from other Geography MSc programmes or from outside Geography subject to availability and approval from the MSc programme convenor
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15 credits |
In Term 3, students on the MSc Programme embark on a Dissertation (60 credits).
Please note these may be subject to change.
People
James is Director of the UCL Q-Step Centre and Deputy Director of the ESRC Consumer Data Research Centre. His research interests span the analysis and visualization of spatially-referenced population datasets. He is co-author of the best selling London: The Information Capital and Where the Animals Go. |
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![]() Jo Wilkin Jo joined UCL Geography in 2020 after completing an ESRC funded PhD on mining Call Detail Records to estimate social connectivity for Disaster Resilience Estimation, based within the Worldpop research team at the University of Southampton. Her research interests focus on the creation and use of innovative geospatial datasets for insight within Disaster Risk Reduction. |
![]() Mirco Musolesi Mirco joined UCL in June 2015. He is also a Turing Fellow at the Alan Turing Institute. At UCL he leads the Intelligent Social Systems Lab. Before joining UCL, he held research and teaching positions at Dartmouth College, Cambridge, St Andrews and Birmingham. Over the past years, the focus of his work has been the design of next-generation intelligent systems mainly based on computational and mathematical models of human behaviour and social dynamics. |
![]() Paul Longley Paul has worked at UCL since July 2000, since when he has co-author of four editions of Geographic Information Science and Systems (with translations into Czech, Korean, Mandarin, Polish and Portuguese) and has supervised more than 50 Ph.D. students. Since February 2014 he has directed the Consumer Data Research Centre at UCL and has taken a lead in its development of geo-temporal demographics. |
![]() Rory Coulter Rory joined UCL Geography in 2017 after completing an ESRC Future Research Leaders project on young people’s homeownership. His research uses longitudinal datasets to analyse the types of homes and neighbourhoods people move through over the life course. |
![]() Stephen Law Stephen has worked at UCL since 2017 where he completed the Alan Turing Institute EPSRC fellowship. His research interests include spatial network analysis, space syntax, house price modelling, machine learning and computer vision. |
Fees and funding
Information on fees and funding can be found on the main UCL website.
Applications
You can apply for a place on this Programme via UCL Admissions (in the application form, please select 'Geography' as the department and 'Postgraduate Taught' as the Programme Type).
For any enquiries or more information, please e-mail geog-masters@ucl.ac.uk.
Careers
There is a wide interest in spatially referenced datasets and how to analyse them in a range of different industries. The skills taught in this programme are applicable to the following careers: GIS, marketing & business intelligence, location planning, digital health & epidemiology, data science, resource management and exploration and many more. Furthermore, MSc MSc Social and Geographic Data Science provides an ideal foundation for PhD research.
Take a look at our Careers page to see where some of our students have gone on to work.