How do you apply an algorithm or numerical method to a problem? What are the advantages? And the limitations? Understand the theory and application of nonlinear programming. Learn the principles of good modelling and know how to design algorithms and numerical methods. Critically assess issues regarding computational algorithms.

In this module you will learn what underpins the algorithms used where variables are integer and apply these algorithms to solve integer and mixed integer problems with cutting-plane algorithms.

Why are arbitrage arguments important in modern finance? How can a binomial model evaluate derivatives? What are the main models for interest rates? Understand the mathematical techniques underlying the modelling of derivative pricing. Acquire skills in the development of pricing and risk management. Explore stochastic methods and credit risk.

Artificial Intelligence is the science of making computers and machines to produce results and behave in a way that resembles human intelligence. This multidisciplinary activity involves the knowledge of different disciplines such as computer science, Mathematics and statistics, but also includes important elements from philosophy, logic and even psychology. Nowadays, AI is well embedded in our society from self-driving cars to spam filters, and from finance trading to video games. All predictions state that more and more of our society will depend on this technology with the consequent transformation of our society and economy. The impact of AI affects any discipline and therefore it is important for everyone to understand its principles, applications and limitations. This module is suitable for any student regardless of their background. This module will provide you with a broad overview of AI, as well as more detailed understanding of core concepts and models. We will follow an approach both theoretical and practical, describing the theory and fundamentals of machine learning models, as well as showing how to implement them and their applications.

Are you interested in understanding how AlphaGo was able to beat a top Go player? In this module, you will learn about the models behind successful stories of Reinforcement Learning, where a machine (agent) makes sequential decisions to reach an optimal goal. The lectures will be complemented with Lab sessions where we will take advantage of the Open AI Gym environments, allowing us to train our agents to perform tasks such as playing videogames (Atari) and more.