Master option pricing with Python by turning financial theory into practical pricing models, analysis, and real-world applications.




Learn options trading fundamentals and prepare financial data before implementing Black-Scholes, binomial and trinomial trees, Monte Carlo simulation, implied volatility models, and option Greeks. Advance to exotic options, risk-neutral valuation, and numerical pricing methods while learning how to test and evaluate your models.




Practice what you learn through real-world options pricing across asset classes and machine learning applications. Understand trading strategies, portfolio optimization, hedging, and risk management, and discover how option pricing models fit into quantitative finance and trading workflows.




By the end, you will be able to build, test, and apply Python option pricing models and understand how AI/ML and emerging techniques are shaping the future of quantitative finance.