Imperial College London

This course enables students to understand one of the core purposes of finance: the setting of prices in a market. The first half of the course works at a market-level, dealing with risk-management and diversification. The second half of the course works at the security-level, thinking about bond, stock, and derivative valuation.

This course explores how machine learning addresses the problem of how computers can learn and extract information automatically from data. It further explores the methods used in artificial intelligence, data mining, and adaptive system design. Students learn how machine learning is used in most disciplines where data is available, including, e.g., electrical engineering, computer science, or medicine. The course introduces students to the theory and practice of modern machine learning methods.

This course presents students with a comprehensive introduction to advanced topics in Linear Algebra as needed in the more advanced literature on Signals, Signal Processing, Systems and Control. The emphasis is on fundamental notions related to vector spaces, inner product spaces, normed spaces, matrix algebras, and computations with matrices.

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. 

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.

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 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. 

This course examines the knowledge, skills, and experience in starting up an innovative business, in looking for critical funding and in structuring a deal to make a business viable. The course is geared towards students who want to develop an entrepreneurial mindset, want to undertake innovative business cases, or have a general interest in start-ups.