University of Edinburgh

This course looks at popular fiction in the late 19th, 20th, and earlier 21st centuries to see how suspense narratives are encoded in society. Students examine detective stories, espionage fiction, ghost stories, horror fiction, and thrillers to see how ideologies are both reinforced and challenged by popular fiction. The course considers the emergence and development of the genres, explores the allure of fear, and examines ideas about class and gender in relation to the practices of reading and the circulation of texts. Though primarily focused on literature, the course is supplemented by optional film screenings and discussions. The course introduces students to the study of popular fiction as it both contributes to and is produced by ideology. The comparison of generically-linked texts from either end of the 20th century encourages discussion of the changes in social history of the period. The chosen texts guide students into a basic understanding of important theoretical ideas: the unconscious, post-Marxist concepts of ideology, Foucauldian ideas about surveillance and power. The course encourages discussion of a wider range of film and general reading and an understanding of students' own cultural environment.

This course is an introduction to blockchain systems and distributed ledgers, the relevant cryptographic tools and smart contracts programming.

This course examines concepts and debates relating to public health, health inequalities, and health policy in a global context. It enables students to understand the policy making process, to analyze the roles of key health policy actors, and to consider the relationship between evidence and policy in relation to health.

This course asks and answers the question "what are data, and how do they come to be?" The story of data reveals the moral and political values that shape human practices of counting, measuring, and labelling reality, and helps us better understand the growing power of data in today's world. Designed to engage students across the disciplines, this introductory course offers a foundational integration of basic concepts and methods of data science with the historical and philosophical context that reveals their ethical and political dimensions as inseparable from their scientific value. The course draws from the disciplines of philosophy, sociology, history, mathematics, computer science, and the design arts to build up a more comprehensive picture of how data are constructed, interpreted, shared, and used for a growing range of scientific, commercial, public and creative purposes.

This course focuses on computation in the nervous system. Students are introduced to basic neuroscience concepts, learn about how computational models are used to simulate processes in the brain, and learn about theories for how the brain processes information and performs computations. Topics include an introduction to basic neuroscience concepts, models of neurons, neural encoding, neural decoding, information theory, network models, and plasticity/learning. The course is delivered through lectures and computer labs.

The course equips students with the skills necessary to understand, critically assess, and undertake the research design process relevant to their degree. Students gain a good grasp of the behavioral assumptions in social science research, knowledge of a range of data collection methods (and how to assess the appropriateness of each), as well as the steps within a successful research project design. More specifically students learn how to choose a topic, formulate a research question and hypotheses, select cases, navigate measurement issues, and undertake a range of data collection methods.