The MSc Geographic Data Science programme is aimed at those who wish to develop their skills in the analysis of quantitative data to answer research questions on spatial and geographic social science topics. The programme will suit you if you are interested in research for academic or policy purposes, have a background in economics or other quantitative social science and are interested in developing your technical skills in analysis of spatial data.
The programme combines courses in the Department of Geography and Environment, with options in data science and programming from the Department of Statistics and Department of Methodology.
Skills in obtaining, managing, visualising and analysing data (data science) are in high demand and the programme combines a training in the application of these methods and the use of geographical information systems (GIS), with the chance to study topics in urban economics, economic geography, environmental economics or planning. The culmination of the programme is a dissertation in which you investigate your own research topic using the data science and GIS methods you have studied on the course.
Upper second class honours degree (2:1) or equivalent with background in economics or another quantitative social science, and good analytical, quantitative and technical skills.
Competition for places at the School is high. This means that even if you meet the minimum entry requirement, this does not guarantee you an offer of admission.
For fees and funding options please visit website to find out more
The School recognises that the cost of living in London may be higher than in your home town or country, and we provide generous scholarships each year to home and overseas students.
This programme is eligible for needs-based awards from LSE, including the Graduate Support Scheme, Master’s Awards, and Anniversary Scholarships.
Many graduates from this programme go on to do PhD degrees, while others enter a wide variety of employment including consultancy, the public sector and education.
Please visit website for module details
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