London School of Economics

This course introduces students to the core ethics concepts needed to build better technology and reason about its impact on the economy, civil society, and government. In the first half of the course, students consider ethical questions raised by different steps in the data science pipeline, such as: What is data, and how can we design better (ethical?) data governance regimes? Can technology discriminate? If so, what are promising strategies for promoting fairness and mitigating algorithmic bias? Can we understand black-box AI systems and explain their decisions? Why is it morally important that we do so? In the second half of the class, students consider ethical questions raised by the use of AI systems to manage our work, political, and social lives.

The course familiarizes students with the basic principles of law, so that they can apply them to a wide range of commercial transactions, in the light of the policy objectives that legal regulation pursues, and with an understanding of the context of commercial transactions in which the law operates. 

This course outlines the structures of the European Union, its law-making processes, judicial architecture, and its most important policy domains. It does so by focusing on both the law of European integration and the political, social, and cultural context within which it operates. Students tackle questions about the dynamics and direction of integration, including the existential challenges posed by Brexit, the rule of law crisis and the refugee crisis.

The primary focus of this course is on the core machine learning techniques in the context of high-dimensional or large datasets (i.e. big data). The first part of the course covers elementary and important statistical methods including nearest neighbors, linear regression, logistic regression, regularization, cross-validation, and variable selection. The second part of the course deals with more advanced machine learning methods including regression and classification trees, random forests, bagging, boosting, deep neural networks, k-means clustering and hierarchical clustering. The course will also introduce causal inference motivated by analogy between double machine learning and two-stage least squares. All the topics are delivered using illustrative real data examples. Students also gain hands-on experience using R or Python (programming languages and software environments for data analysis, computing and visualization).

This course covers the following: 1. study of 20th-century British literature (prose, poetry, and drama) in its socio-political context; study of individual authors (in weekly lectures) 2. study of major cultural themes running through the century, e.g., literature of war; imperialism; feminism; modernism; postmodernism; political writing, 3. several trips to theatre productions during the year, 4. extensive use of archive recordings of authors, and video.

This course discusses some central empirical and theoretical questions in the field. It begins by examining classic comparative debates about the relationship between the development of states and nations on the one hand, and the rise of capitalism and democracy on the other. The course examines the impact that social cleavages have on parties, elections and other political institutions in a number of different countries. It also examines the strength and political impact of both labor movements and other important social movements. Additionally, the course examines why similar countries can develop very different social and economic policies. In addition students examine some of the founding writings of Marx and Weber and critically assess the use of political concepts. Throughout the course students consider some of the main theoretical approaches that are used in the study of political sociology.

This course examines, from a philosophical perspective, the ways in which recent developments in genetics and neuroscience challenge our conceptions of what we are — and what we could become.

The course provides an introduction into monetary and financial history from the 18th century to the present day. It examines the main developments in international monetary architecture and the global financial system since the Glorious Revolution. The course introduces students to major concepts of money and finance (financial development, financial integration, monetary policy, banking crises etc.) and to provide a long run perspective to the current policy debate.

The course covers key statistical methods and data analytic techniques most relevant to finance. Hands-on experience in analyzing financial data in the “R” environment is an essential part of the course. The course includes a selection of the following topics: obtaining financial data, low- and high-frequency financial time series, ARCH-type models for low-frequency volatilities and their simple alternatives, Markowitz portfolio theory and the Capital Asset Pricing Model, concepts and  practices in machine learning as applied in financial forecasting, Value at Risk. The course covers classification techniques using random forests and simple trading strategies if time permits.

Throughout the 18th century, thousands of young British men and women embarked on extensive journeys to continental Europe – an activity known as the Grand Tour.  This course explores who these people were, where they went, and the reasons for their expeditions.  For some, the Tour was the final stage of formal education; to others an opportunity for sexual adventures and pleasure-seeking. The course discusses the practical challenges of 18th-century travel, the political, religious, and cultural contexts of the Tour, as well as the key places to visit and the reasons for their popularity.  It also considers what the Tourists brought back with them: from physical artefacts for public and private collections, to new ways of seeing and understanding the world. The course introduces students to the actual writings of the Tourists, showing how they experienced international travel and shaped the modern tourist industry.