The goal of this course is to provide you with a quick but solid introduction to a theoretical foundations of machine learning.

The LAT Summer Trading School Programme has been designed for school and university students looking for a more vocational approach to finance and trading. Based online, on the LAT trading floor or via a blended combination, students will learn about different financial markets and how they are traded, as well as the practicalities of trading from a fundamental or technical perspective.

Getting things wrong is part of what makes us human, and our natural intelligence helps us learn from our mistakes. Reinforcement learning is an area of machine learning which enables artificial intelligence to learn from its mistakes as well, for example allowing a robot to use trial-and-error to interact with a new environment and achieve an objective. This advanced course examines the fundamentals of reinforcement learning and explores the varied applications of dynamic programming methods.

Deep Unsupervised Learning is an exciting emerging area of research in the field of artificial intelligence and machine learning, in which the goal is to develop systems that can learn from unlabelled data. Such systems closely mimic natural human intelligence by finding patterns in data without instructions on what to look for.

From self-driving cars and augmented reality to intelligent medical imaging helping doctors identify diseases more quickly, computer vision is a rapidly growing field within artificial intelligence and machine learning. In this course, students who are already familiar with the key theoretical foundations of artificial intelligence and machine learning will dive deeper into the exciting capabilities of this area of research and its applications.

In our age of burgeoning smart technology and automation, we are already seeing the transformative potential of Artificial Intelligence and Machine Learning in fields as diverse as finance, medicine, and manufacturing. This course offers a hands-on introduction to this future-focused area of research.

Advanced Artificial Intelligence and Machine Learning: Natural Language Processing is a course that delves into the theoretical concepts of NLP, exploring its current applications and envisioning the potential future uses in diverse domains. The course highlights the significance of NLP in our daily lives, emphasizing its integration through predictive text, translation tools, and smart devices, showcasing the immense future potential within this exciting area of research, particularly evident in large language models like Chat-GPT.

This course provides a comprehensive overview of the key concepts related to monetary policy and central banking and their significance in understanding the economy, including the Monetary Transmission Mechanism, the New Keynesian Model, Financial Frictions, Central Bank Design, and Central Bank Communication.

Most macroeconomic outcomes depend on people’s beliefs about the future. Different models of expectation formation will, as such, have different implications for macroeconomic dynamics. This short course aims to introduce you to the main methodological tools used in behavioural macroeconomics, while at the same time providing a survey of the main questions and answers given in the modern literature.

This course provides a comprehensive analysis of the challenges faced by policymakers in dealing with international financial shocks, and the evidence on the dilemma vs. trilemma debate. It covers a range of topics including a model for international financial shock transmission, the Euro Area's current account imbalances and debt crisis, and the impact of capital flows on inequality.

While the world has been moving increasingly towards greater inter-connectivity through trade, infrastructure, communications, and migration, criticism of ‘globalisation’ has been growing ever louder. This wide-ranging course explores the process of globalisation, its macroeconomic implications, and the role of international organisations such as the United Nations. You will examine some of the responses to globalisation, from populist political movements like Brexit and Trumpism to diverse transnational social movements such as Black Lives Matter and the Arab Spring of 2011. In so doing, the programme will engage with ethical and theoretical constructs to help us to understand better the thinking behind the differing dynamics we are examining. This course is perfect for students seeking to understand some of the most significant political phenomena of our time.

In this course, we are going to unpack the key driving factors behind the ascent of the digital economy as well as policy challenges brought by this rapid rise. We are going to talk about how firms can build up and monetise network effects, and how platforms make their pricing and stocking decisions. We will look into the economics of search engines, the strategic design of search algorithms and search pricing. We are going to discuss the competition policy response to the rise of digital platforms and, in particular, focus on consumer data and privacy.

Through a mixture of theory and substantive applications, this short course will introduce you to important issues that are typically ignored in the first course in causal inference.

This course teaches key methods for solving modern macroeconomic models, including those able to account for agent heterogeneity. Participants will obtain detailed theoretical knowledge of and hands-on experience with linearization techniques, non-linear solution methods and approaches for solving heterogeneous agent models with and without aggregate uncertainty.

This course will cover two major empirical topics that play a central role in studying the productivity and market power of firms: the estimation of production functions, and the estimation of price-cost markups. There have been important developments in both areas in recent years, which will be outlined and discussed in the course. Our focus will be on the use of micro datasets that are widely available, either from company accounts for individual firms or from the census of production surveys for individual business establishments.