Machine learning: Tools and applications for policy

Programme Description

It is hard to name a sector that will not be dramatically affected by machine learning or even artificial intelligence. There are many excellent courses that teach you the mechanics behind these innovations, helping you develop an engineering skill set. This course takes a different approach. It is aimed at people who want to deploy these tools, either in business or policy, whether through start-ups or within a large organization. While this requires some knowledge of how these tools work, it is only a small part of the equation – just as knowing how an engine works is a small part of understanding how to drive. What is really needed is an understanding of what these tools do well and what they do badly. This course focuses on giving you a functional, rather than mechanistic, understanding. By the end, you should be an expert at identifying ideal use-cases and thereby well-placed improve analysis and policy using machine learning.

This Florence School of Banking and Finance course thus aims to provide an overview and understanding of popular Machine Learning (ML) techniques, understand the opportunities and limitations of these techniques and be able to interact with the experts. In practical terms you will work hands-on with ML/AI methods in Python, demystify the black boxes and prime you so that you can continue to learn by yourself.

Research Themes

• Statistical and econometric methods