Students on programmes in the Department of Geography can pursue a suite of modules in Spatial Data Science.
This offers undergraduates outside of Computer Science a unique opportunity to learn the fundamentals of data science using the Python programming language, combining these insights with theory and knowledge learned elsewhere in their Geography or Environmental Science programme.
Image source: ChatGPT
Data science is the interdisciplinary field of using statistics, programming, and machine learning to analyse and visualise large datasets, revealing patterns and insights that can solve complex problems, such as mapping climate change, managing public health systems or analysing customer behaviour.
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In turn, spatial data science combines geographic concepts with data analysis to explore, visualise, and model spatial patterns and relationships, enabling insights into real-world issues like urban planning, environmental change and mobility patterns.
Our spatial data science modules are designed to build one on top of the other so that it is possible to complete the pathway despite having little or no prior experience in computer programming.
Walkability Index using Open Street Map Data (left) and visualisation of house price changes in London (right)
We believe that this suite of modules not only offers our students a valuable set of tools for undertaking research at undergraduate and graduate levels but also creates a competitive advantage in today’s job market by helping students stand out from the crowd.
The aim is to start students down the path to being either a practising (spatial) data scientist or a valuable bridge between the ‘number crunchers’ and the rest of an organisation, whether it’s an NGO, private company or public institution.
