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Description
This module provides students with an introduction to (Python) programming and data science through a mix of videos, demonstrations, practicals, discussions, and coursework built around an applied spatial analysis problem using real-world data. The module is intended to complement Quantitative Methods and Geographic Information Systems by showing how geographic and quantitative concepts are applied as part of a larger piece of spatial data science analysis.
However, attention in class and in the assessments will also be given to critical readings intended to develop an appreciation of real-world (geo)data, and their biases and limitations. These seek to ground the student鈥檚 newfound skills in an understanding that 鈥榯he data do not speak for themselves鈥� and of the role of the spatial data scientist in selecting and developing evidence to support decision- and policy-making. Students should therefore be looking for ways to use this module to integrate, reinforce, and generalise their understanding of how a spatially-aware data science supports critical analysis and good judgement.
Over the term we will assemble an end-to-end data science 鈥榩ipeline鈥� incorporating the principal tools used in industry and academia, and leading through data cleaning, transformation, and visualisation to interpretation and presentation. We will see how these components are situated within a wider disciplinary 鈥榯errain鈥� entailing debates around the construction and validity of different types of knowledge. It is hoped that students will not only find ways to apply what they have learned here to support their research and studies, but also to become familiar with core tools employed by practicing geographic and spatial data scientists in ways that further post-graduation employment opportunities.
Module deliveries for 2024/25 academic year
Last updated
This module description was last updated on 8th April 2024.
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