United Kingdom - England

This course begins by prompting students to reflect on what happiness means to them. What is happiness? What is it for? Does it matter? How can we measure it? The course explores a variety of ‘theories’ of happiness, asking students to think about what happiness means to them in their lives and communities. Through discussions, research, and reflection students are exposed to different interpretations and understandings of happiness. 

This course focuses on data about connections, forming structures known as networks. Networks and network data describe an increasingly vast part of the modern world, through connections on social media, communications, financial transactions, and other ties. The course covers the fundamentals of network structures, network data structures, and the analysis and presentation of network data. Students work directly with network data and structure, and analyze these data using R.

This course provides an introduction to the management accounting and financial control concepts that are used in strategic decision-making, in order to effectively perform in a competitive business environment. Covering issues such as technology and digitalization, corporate strategy, marketing, and modern cost management tools, students critically analyze how these tools can be used to increase performance.

This course introduces students to the study and history of these economic inequalities. It is a detailed survey of the key evidence on inequality, both contemporary and historical, and the sources and methods used to measure it. Students learn how to critically interrogate the quality of inferences from such evidence. They explore the dimensions of inequality along historical, contemporary, spatial, ethnic, and gender lines, drawing on research in economic history, economic geography, and sociology. 

The course offers students the opportunity to apply their knowledge in a major group design project which considers the full design process; from the client brief to the demonstration of a prototype. You must work systematically from high-level goals to detailed design, drawing upon knowledge and skills learned in other courses. Communication with the client occurs throughout and involves an assessed presentation, report, and demonstration. Team-working is crucial, as groups must develop several subsystems in parallel and integrate them together, as well as carry out non-technical tasks such as documentation and cost management. In addition, students develop problem solving skills, project and time management, and communication.

The course focuses on the differing approaches and styles used by global media. Students investigate press and journalism business models, issues of globalization, and examine cross-national differences in terms of ethics, media content, and access to creative industries. It also considers theories around social change and globalization.

This course introduces students to the fundamentals of deep learning and illustrates how it is contributing to the practical design of intelligent machines. Deep learning is currently the most active area of research and development and in high demand for experts by hi-tech start-ups, large companies as well as academia. It is the preferred approach for modern AI and machine learning in any domain. This course demonstrates how deep learning techniques enable us to automatically extract features from data so as to solve predictive tasks, such as speech recognition, object recognition, machine translation, question-answering, anomaly detection, medical diagnosis and prognosis, automatic algorithm configuration, personalization, robot control, time series forecasting, and much more.

Economics provides us with a useful set of tools for analyzing the world and aiding decision-making by businesses and governments. This course gives students an overview of many of these tools and of the insights that can be obtained with them, concentrating on those most relevant to businesses. This means that most of the lectures are on microeconomic topics, looking at the actions of firms and of individuals, but the course concludes with some coverage of macroeconomic problems and policies, looking at the economy as a whole. Upon completion of this course, students can intelligently discuss and analyze current events in business and 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.

This course teaches students to use finite element programs in a practical way to solve problems in linear elastic stress analysis. Upon completion of the course, students are able, in a later industrial setting, to undertake the analysis of real problems with a fair understanding of sensible modelling procedures. In support of this, the course is split into two stages: the theoretical study of the finite element method, with emphasis on understanding what goes on inside a typical, modern, commercial program; and practical experience in analysis using an industry-standard, interactive, finite element program.