Python Data Analysis for Algorithmic Trading

Are you interested in algorithmic trading but don't know where to start with market data? Success in automated trading begins not with complex execution systems, but with the ability to analyze and manipulate financial data. This text-only course guides you through the foundational steps of using Python for financial data analysis. You will learn how to import historical market data, clean messy financial datasets, calculate technical indicators, and evaluate basic patterns. By the end of this course, you will have the practical skills needed to transform raw market feeds into structured, actionable data ready for backtesting. What you'll learn: - Understand the core concepts of algorithmic trading and financial data structures - Retrieve and clean historical market data using modern Python data libraries - Calculate key technical indicators and moving averages to identify trends - Apply modern Python conventions, including type hints and virtual environments, for clean code - Analyze price movements and asset returns using statistical methods - Prepare structured datasets optimized for strategy backtesting We start with the essential terminology of financial markets and basic Python setup, then move step-by-step through data manipulation, formatting, and technical analysis formulas. You will practice through structured written explanations and realistic data-handling scenarios. This course is designed for beginners who are new to algorithmic trading and want to build a strong foundation in financial data analysis. No advanced programming or finance background is required. Start your journey into quantitative finance and master the data skills behind algorithmic trading today.