All courses are postgraduate (SCQF Level 11) at the Edinburgh Futures Institute , University of Edinburgh.
Hands-on exploration of diverse real-world datasets to understand and analyse problems of inequality in society. Students learn to relate, visualise, and model numerical data through interactive notebooks, culminating in an intensive project phase.
Examines how information spreads and shapes public opinion in digital environments — from rumours on messaging platforms to bot-driven political discourse — developing students' capacity to critically evaluate evidence and argumentation.
Data-driven evaluation of climate and sustainability challenges facing urban and rural environments, equipping students with frameworks and methods to assess land-use and city-planning decisions against sustainable development goals.
Explores how urban mobility data can help policy-makers design sustainable transport systems centred on active travel. Covers data collection, analysis, and visualisation in the context of global sustainability and UN-Habitat targets.
Introduces the theory and practice of computational text analysis using Python, designed for social researchers regardless of prior programming experience. Topics include text preprocessing, corpus analysis, and visualisation for social science questions.