London School of Economics

This course introduces students to key concepts and techniques used in operations management, and their practical applications. The course covers a range of topics related to manufacturing and service operations such as operations strategy, sustainability, process design and analysis, supply chains, inventory management, lean operations, and quality control.

This course introduces students to social science theories, research, and application related to understanding human behavior in the workplace. This course considers "the people side" of business and management. Topics include personality and performance, managerial decision-making, motivating others, fairness in organizations, the multicultural workplace, power and influence, the adaptive leader, and team leadership.

This course develops beginner to intermediate Russian language skills in a dynamic and communicative way. The course develops all four language skills (i.e. speaking, listening, reading and writing) through individual and group work, topical discussions, and authentic and web-based multi-media materials. The focus is on accuracy as well as communication that advance students’ language competence, transferable skills, and cultural awareness.

This course teaches students how to collect and handle date in a hands-on manner. The first few weeks of the course cover theoretical concepts through traditional lectures, but then the format shifts to a practical approach. Live coding demonstrations are used to guide students through the material, which can be followed in real-time. Python is the primary programming language used in staff-led lectures and classes, but students are also permitted to use R for their assignments if they prefer.

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.