London School of Economics

This course considers how we understand and explain the difference between things with minds and things without. This is the central question of the metaphysics of mind. Increasingly, philosophers who engage with this question aim to give a naturalist account of the mind: one that fits into the picture of the world offered to us by the sciences. But many features of the mind – including, in particular, conscious experience – fit uneasily into this naturalistic world view. This course familiarizes students with the key debates in this area.

The course focuses on the fundamental principles of effective manipulation and visualization of data. It covers the key steps of a data analytics pipeline, starting with formulation of a data science problem, going through manipulation and visualization of data, and, finally, creating actionable insights. The topics covered include methods for data cleaning and transformation, manipulation of data using tabular data structures, relational database models, structured query languages (e.g. SQL), processing of various human-readable data formats (e.g. JSON and XML), data visualization methods for explanatory data analysis, using various statistical plots such as histograms and boxplots, data visualization plots for time series data, multivariate data, and graph data visualization methods.

The course considers how "things" enter into and mediate everyday social relations and practices. Students consider all aspects of the social life of things, from design and production through use, consumption, and everyday practices. This allows them to address a range of long-standing theoretical and political concerns within sociology such as the role of objects and materiality in social life; social organizations of objects and exchange, such as consumer culture; design, technology, and innovation; and the socio-political status of "everyday life" itself. At the same time, there is a strong methodological emphasis: not just how do we study objects in everyday life, but how might such studies impact on social research more generally.

Students in this course explore some of the important conceptual and philosophical questions underlying physics and finance, like: How are assumptions about randomness compatible with observed forms of determinism? How is it possible to seek truth using statistical theories? What does it mean to be an atom? How does the quantum world differ from the everyday world? What explains why physical models have unexpected applications in finance? To what extent do such applications help to underpin how the prices of financial instruments are set? This course will proceed at a conceptual level that is suitable for students of all backgrounds: no background in physics is needed, and there is no advantage to having one.

The course covers the role of data, information, and knowledge within management; the evolution of digital management practices; digital business strategy; information systems development and organizational change; artificial intelligence and distributed ledger technologies; information systems outsourcing; and IT infrastructure including cloud computing, and digital platforms.

This course explores key topics in moral and political philosophy. Students consider some of the key questions at the center of these disciplines. 

This course explores the main developments in monetary financial history from the 9th to the end of the 20th centuries, taking the students from the simple beginnings of medieval European monetary history to the complex financial arrangements of the modern world. The first part of the course covers the emergence of money and finance from the medieval ages to the early modern period. The second part examines the main developments in the global financial system since the 19th century. Students discuss and compare historical developments in major European and non-European countries (England, Spain, Italy, France, Germany, USA). The course teaches students the main concepts of money and finance such as financial development, financial integration, monetary policy, banking crises etc, and provides a long run perspective to the current policy debate.

This course develops theoretical and empirical understanding of spatial economic processes in order to study and evaluate a wide range of issues and policies. Particular emphasis is put on regional economies, business and worker location decisions, focusing in particular on models of the location of economic and innovation activity with a particular emphasis on regional economies. The course analyzes the New Economic Geography theories and the agglomeration of economic activity, with a particular focus on EU integration as a testing ground. Students also look at the global and local knowledge economy, focusing on core aspects of a society based on knowledge and technical progress and how this proceeds hand in hand with the enlargement of markets and the intensification of exchange. Students explore the seeming contradiction that geographically localized knowledge may be increasingly significant just as so much of our world becomes more globalized.

This course is an introduction to macroeconomic analysis. Students study how countries’ economic performance is determined in the short and the long run. Students learn about why we observe economic growth and development for some countries but not for others, and why economic activity fluctuates over time (booms and recessions). The course covers the role of policy and how it affects the economy. Emphasis is given to concepts and tools used by macroeconomists in the analysis of macroeconomic phenomena.