MSc Geographic Data Science and Spatial Analytics
Bristol, United Kingdom
DURATION
1 up to 2 Years
LANGUAGES
English
PACE
Full time, Part time
APPLICATION DEADLINE
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EARLIEST START DATE
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TUITION FEES
GBP 31,700 / per year *
STUDY FORMAT
On-Campus
* overseas full-time tuition
Introduction
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 (THE 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.
You will master data science and machine-learning algorithms, tools, and data structures, and apply them to understand core theories and concepts in urban analytics and city science. 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 concepts and principles around scientific computing and data infrastructure and use them to model smart cities and urban digital infrastructure.
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.
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Admissions
Postgraduate Online Events
from 25th November 2024- 4th of December 2025
Curriculum
You will take four compulsory units and select two optional units from the list of postgraduate units offered by the School of Geographical Sciences.
A key component of the programme is the dissertation, which is well aligned with the programme's philosophy. Dissertations will be written in a paper format following the principles of reproducibility - for instance using open-source computational notebooks such as RMarkdown/Jupyter.
The bulk of the dissertation work will take place during summer months. The dissertation will provide you with practical experience of formulating, designing, and undertaking a substantive and original piece of geographic data science research. You will be introduced to key principles of research design and research ethics through intensive training in this unit.
Unit names
- Dissertation: MSc Geographic Data Science and Spatial Analytics
- Data Science and Machine Learning in Geography
- Geographic Information Retrieval and Integration
Non-ESRC-funded students must also take the following units:
- Urban Analytics and City Science
- Introduction to Scientific Computing
ESRC-funded students must also take the following units:
- Mapping and Modelling Geographic Data in R
- Research Design, Digital Methods and Data Skills
Non-ESRC-funded students select 40 credit points from the following:
- An Introduction to GIS and Remote Sensing for Environmental Policy and Management
- Mapping and Modelling Geographic Data in R
- Policy and Management Consultancy
- Research Design, Digital Methods and Data Skills
ESRC-funded students select 40 credit points from the following:
- An Introduction to GIS and Remote Sensing for Environmental Policy and Management
- Introduction to Scientific Computing
- Urban Analytics and City Science
- Policy and Management Consultancy
Program Tuition Fee
Career Opportunities
This MSc provides graduates with the skills needed for successful careers as data scientists and data consultants in private and public sector. Students have gone on to work in consultancy and engineering companies, and also governmental and third sector organisations. Top graduates can populate research institutes and think-tanks and support the advancement of Geographic Data Science.
Program Admission Requirements
Show your commitment and readiness for Grad school by taking the GRE - the most broadly accepted exam for graduate programs internationally.