University College London

Despite recent societal changes, people with disabilities, chronic illnesses, and/or neurodivergence are still underrepresented in society, popular culture, medical and academic disciplines. In this course, students take an autoethnographic, reflexive approach to exploring disabilities, chronic illnesses, and neurodivergence in society in general by considering representations in film, literature, and media, by studying the social barriers experienced, by learning about equality and social justice and by exploring different approaches to disability and advocacy.

This course surveys the growing subfield of urban political ecology. In particular, it focuses on the material and social flows of ‘stuff’ that circulate to, through, and beyond the city. Water, sewage, electricity, garbage, plastic, carbon, and much more are all pumped, diverted, quarantined, cleansed, financed, regulated, produced, and consumed via cities. This ‘metabolism’ of material things produces varying qualities and outcomes of urban life. These flows and their outcomes are the course’s central focus, framing as urban metabolism the complex, uneven, and surprising journeys, infrastructures, transformations, politics, histories, labor, and expertise required for these flows. Drawing on a diverse set of academic, journalistic, video, textual, and audio course material, the course traces the pathways of material things through cities and their hinterlands worldwide, unpacking how their flows are constructed and regulated, financed, and managed, and contested and politicized.

Data Science is an exciting new area that combines scientific inquiry, statistical knowledge, substantive expertise, and computer programming. One of the main challenges for businesses and policy makers when using big data is to find people with the appropriate skills. Students taking this course are introduced to the most fundamental data analytic tools and techniques, learn how to use specialized software to analyze real-world data and answer policy-relevant questions.

This course introduces students to advanced statistics, applied to the biological sciences. It introduces more advanced linear and generalized linear models, as well as approaches to model building and comparison. It also covers applications of linear models to large-scale genomic data, programming, permutation-based tests, power analysis and multivariate statistics. In addition to providing the theoretical background of the approaches covered, the course puts much emphasis on practical implementation. Lectures are accompanied by weekly practical sessions in which students will work through analyses in the statistical software R, the standard in much of biological computing. 

The course develops students’ psychological literacy through the cycle of enquiry and evidence. Students are introduced to key conceptual issues, methodological approaches, and significant findings in scientific psychology, their historical background, and the kinds of empirical evidence on which these findings are based. Students take simple questions, and cut across traditional disciplines looking for answers.

This course enables students to apply economic principles and models to understand the role of money and banking in the economy and to critically evaluate current debates on competition and regulation in the banking sector. The course studies the role of banking in the financial system and in the wider economy; the economic theory of bank intermediation; economic models of how banks make lending decisions in different market structures; strategies adopted by banks to address risk, with particularly reference to informational asymmetries; economic assessment of competition in banking, considering price and non-price strategies; banking regulation and government intervention in the banking sector; and current debates on the role of government and future of regulation for the sector.