The amount of data available to manage risk in a portfolio as well as the information needed to perform a thorough financial analysis of a company grow at an ever increasing speed. Moreover, data can no longer be gathered from one single source of information.

This practical programme covers key techniques – including several aspects of supervised and unsupervised machine learning – that you can use when mining financial data.

Most exercises and case studies are illustrated in Python, allowing you to learn how to work with this flexible programming language.