12 monthsProgramme duration
32,600 GBPTuition Fee/year
27 Aug, 2026Application Deadline
SepStarting Month
Programme overview
Main Subject
Geography
Degree
MSc
Study Level
Masters
Study Mode
On Campus
Are you passionate about using data and analytics to improve cities and solve spatial problems? The MSc in Geographic Data Science and Spatial Analytics will help you to achieve your ambitions. Join a School ranked first in the UK for 'Geography and Environmental Studies' research (Times Higher Education analysis of REF 2021) and learn how to utilise cutting-edge tools and methods from the data science domain to analyse spatial data in order to tackle challenges spanning across various spatial scales: from neighbourhoods and cities to regions and supra-national systems.
Whether your background is in Geography, Planning, or Social Sciences more broadly, or in numerate subjects such as Computer Science and Engineering, this programme will help you succeed in the dynamic field of Geographic Data Science and Spatial Analytics.
We welcome a diverse array of students from different subject backgrounds seeking to master data science and machine-learning algorithms, GeoAI tools, and data infrastructures, and apply them to understand core theories and concepts in social and environmental sciences. You will be able to employ cartographic and geographic theory and concepts to map and model big geographic data. You will understand the main engineering principles around scientific computing and GeoAI, and use them to help tackle global challenges across disciplines.
The MSc in Geographic Data Science and Spatial Analytics builds upon the Quantitative Spatial Science (QuSS) research group within the School of Geographical Sciences and its longstanding history and excellence in quantitative geography and spatial analysis.
As a student on our MSc programmes, you’ll join a lively School and University community. We host invited speakers in weekly seminars organised by our School’s academic research groups. These friendly events are open to all students and offer you the opportunity to meet other students and leading specialists in a range of subjects. Research groups may also host social events, run specialist workshops and organise reading groups you are welcome to join.
Our postgraduate social calendar is also busy, with social events and activities for members including cinema nights, writing retreats, field visits, and guided tours of cultural institutions. We also organise get-togethers for our students throughout the year to mark the major milestones in your programme and celebrate your success.
Programme overview
Main Subject
Geography
Degree
MSc
Study Level
Masters
Study Mode
On Campus
Are you passionate about using data and analytics to improve cities and solve spatial problems? The MSc in Geographic Data Science and Spatial Analytics will help you to achieve your ambitions. Join a School ranked first in the UK for 'Geography and Environmental Studies' research (Times Higher Education analysis of REF 2021) and learn how to utilise cutting-edge tools and methods from the data science domain to analyse spatial data in order to tackle challenges spanning across various spatial scales: from neighbourhoods and cities to regions and supra-national systems.
Whether your background is in Geography, Planning, or Social Sciences more broadly, or in numerate subjects such as Computer Science and Engineering, this programme will help you succeed in the dynamic field of Geographic Data Science and Spatial Analytics.
We welcome a diverse array of students from different subject backgrounds seeking to master data science and machine-learning algorithms, GeoAI tools, and data infrastructures, and apply them to understand core theories and concepts in social and environmental sciences. You will be able to employ cartographic and geographic theory and concepts to map and model big geographic data. You will understand the main engineering principles around scientific computing and GeoAI, and use them to help tackle global challenges across disciplines.
The MSc in Geographic Data Science and Spatial Analytics builds upon the Quantitative Spatial Science (QuSS) research group within the School of Geographical Sciences and its longstanding history and excellence in quantitative geography and spatial analysis.
As a student on our MSc programmes, you’ll join a lively School and University community. We host invited speakers in weekly seminars organised by our School’s academic research groups. These friendly events are open to all students and offer you the opportunity to meet other students and leading specialists in a range of subjects. Research groups may also host social events, run specialist workshops and organise reading groups you are welcome to join.
Our postgraduate social calendar is also busy, with social events and activities for members including cinema nights, writing retreats, field visits, and guided tours of cultural institutions. We also organise get-togethers for our students throughout the year to mark the major milestones in your programme and celebrate your success.
Admission Requirements
- Applied Statistics
- Mathematics
- Machine Learning
- Data Mining
- Quantitative Geography
- Python or R
- Computer Modelling and Simulation
- Geographic Information System
- Online courses in data science may be considered on a case by case basis.
We will also consider your application if your final overall achieved grade is slightly lower than the programme's entry requirement.
If your achieved grade is lower than our entry requirements, your application may be more likely to receive an offer if you have additional relevant work experience or qualifications. If you have at least one of the following, please include your CV (curriculum vitae / résumé) when you apply, showing:
- Evidence of one year's full-time work experience/internship as a GIS analyst, data scientist or experience in quantitative analytics, urban planning in relevant sectors such as industry, Government or NGOs. Experience must be within the last two years.
- A relevant postgraduate qualification.
English language requirements
If English is not your first language, you will need to reach the requirements outlined in our profile level C.
- Candidates are required to submit references or letter(s) of recommendation for acceptance
- Candidates are required to submit an essay(s) for acceptance
Tuition fees
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