The course is designed to provide a theoretical and practical basis to address some of the most important issues in the context of modern financial markets. It consists of three distinct, but strictly interrelated parts.

A theoretical part developing the main findings and models of applied finance in recent years (in the fields of interest rates, credit risk, counterparty risk and (new!) Machine Learning Techniques ).

An applied part, solving real case examples with the aid of Python programming language. The latter is the very value-added part of the course because it requires the student to solve practical issues faced frequently in the day-to-day work in the financial industry and Python is one of the most used languages both in fintech and data analysis.

A series of monographic lessons with the presence of practitioners of the industry. Already programmed is a lesson held by a practitioner on Data Analytics for financial control in Investment Banking.