Course · Beginner - Market Data Foundations

Learning outcomes

• Handle and clean financial datasets with pandas and NumPy
• Build price and macro time series ready for analysis
• Organize a reproducible working notebook, with basic version control
• Compute common descriptive indicators (return, volatility, drawdown)

This free-access module is designed for anyone who has never combined programming and financial analysis. No prior experience is required: just curiosity about understanding markets through data instead of intuition.

Who it's for

Anyone starting from scratch in programming, or already using spreadsheets to analyze portfolios and wanting to move to a more flexible, reproducible workflow.

What the module covers

• Setting up and organizing a data-oriented Python working environment
• Loading, cleaning and merging price, dividend and macroeconomic series
• Building descriptive indicators: cumulative return, volatility, maximum drawdowns
• Good practices so an analysis notebook can be reproduced by someone else

Format

Short recorded lessons with guided exercises on real sample data, plus a reusable notebook template for the following modules of the curriculum.