Data-Driven Quantitative Stock Investing with Python

Quantitative investing is no longer reserved for Wall Street institutions. With Python, any investor can analyze market data to make systematic, data-driven decisions. This text-only course guides you from absolute beginner to confidently writing Python scripts that retrieve, clean, and analyze stock data.\n\nYou will begin by mastering essential financial terminology, market concepts, and Python data structures. From there, you will learn how to handle real-world financial datasets and translate trading ideas into code.\n\nWhat you'll learn:\n- Understand core quantitative finance concepts, terminology, and market data structures.\n- Retrieve historical stock data using modern Python libraries and financial APIs.\n- Apply data manipulation techniques with pandas to calculate returns, moving averages, and volatility.\n- Build and backtest simple, rules-based trading strategies using historical data.\n- Evaluate strategy performance using key metrics like Sharpe ratio and maximum drawdown.\n- Practice writing clean, modern Python code with type hints and robust data handling.\n\nThis course progresses from foundational definitions to hands-on analysis, ensuring you understand the mechanics behind every line of code. Through clear written explanations and structured practice exercises, you will develop the practical skills needed to analyze the stock market systematically.\n\nThis course is designed for beginners interested in quantitative finance, retail investors wanting a systematic approach, and Python learners looking for practical data analysis projects. No prior financial or programming experience is required. Start your journey into data-driven investing today.