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Who should attend
This programme is designed for professionals wanting to learn about AI in finance and working in the financial services industry, including members of the exchanges and regulatory agencies, and executives who make decisions that affect financial results. To get the most from the three intensive days, you will need a good grounding in finance and statistical techniques.
About the course
AI & machine learning in financial services course overview
Imperial Artificial Intelligence (AI) & Machine Learning in Financial Services programme is a three-day course that explores the role of emerging algorithmic techniques on financial decisions. Drawing on knowledge from Imperial College Business School faculty, industry experts, case studies and your peers, you will apply key elements of artificial intelligence (AI) and machine learning to your organisation, increasing the efficiency and accuracy of decision making.
Knowledge of machine learning in finance
Through this immersive, hands-on training programme, you will gain an understanding of the fundamentals of AI and machine learning and how aspects such as big data apply to financial functions such as fraud detection, lending processes, asset management, risk assessment, regulatory compliance and beyond.
You will walk away prepared to implement what you’ve learnt, ensuring your organisation is maximising the value of its live and historic data.
Gain a good understanding of the main concepts of AI and machine learning
Understand how to operationalise AI and machine learning
Be able to identify key areas to apply AI and machine learning techniques within your teams and workplace
Be able to appreciate the advantages that AI and machine learning techniques can add to various portfolio and risk management strategies
Summary Enrico Biffis is Associate Professor of Actuarial Finance at Imperial College Business School, a fellow of the Pensions Institute in London, and a member of the Munich Risk and Insurance Centre at LMU Munich. His areas of expertise are risk analysis and asset-liability management, with a ...
Summary Personal web page Professor Buraschi’s research interests are in the fields of Financial Economics, Asset Pricing and Derivatives, and Financial Econometrics. Professor Buraschi has previously held at The University of Chicago Booth School of Business as a Visiting Professor of Finance ...
Summary Private Website
Summary Paolo is Professor in Financial Econometrics at Imperial College Business School. He has a summa cum laude degree in economic statistics from Roma and holds a PhD in Econometrics from the London School of Economics. He is also teaching at the University of Rome La Sapienza and has...
Pierre Dangauthier is the head of Quantitative Analytics at Smarkets, one of the leading betting exchanges. He is specialized in systematic market making and machine learning. He received a Ph.D. degree in statistical learning in 2007 from INRIA for a joint work with Microsoft Research Cambridge...
Deeph has extensive experience of working on world leading STEM in academia, industry and government. He is Professor of Practice within Imperial's Business School, Deputy Director of the Institute for Security Science Technology and is co-founder of the UK-Goverment funded Research Institute in ...
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Because of COVID-19, many providers are cancelling or postponing in-person programs or providing online participation options.
We are happy to help you find a suitable online alternative.