Free Python for Finance Course

Start using Python for Finance and learn about some realistic examples.

This training is an email-based training course which is completely free. It cannot teach you Python for Finance thoroughly but it can illustrate some realistic use cases for Python and libraries like pandas and NumPy in a financial context. The different modules are based on a single Jupyter Notebook each which you can download and use on your local machine or which you can execute on the Quant Platform for which free single user accounts are available.

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Financial Data

Module 1 — This module illustrates the use of pandas for working with financial data and visualizing such data.


Module 2 — Using pandas, this module illustrates how to backtest trading strategies in vectorized fashion.


Module 3 — Working with NumPy, this module covers the Markowitz portfolio theory based on portfolio mean and variance.


Module 4 — Using NumPy's random number capabilities, this module shows how to price a European call option based on Monte Carlo Simulation.


Module 5 — This module illustrates some of the most important use cases regarding data storage and retrieval (e.g. CSV files).


Module 6 — Performance is of paramount importance when implementing financial algorithms. This module illustrates how dynamic compiling helps with e.g. nested loops and recursive algorithms.