Quantitative & Algorithmic Trading — A General Introduction with Python
Who it is for: programmers and analysts curious about systematic trading who want a sober, engineering-minded introduction.
You will be able to:
- Load and clean market data and compute returns, volatility and drawdowns
- Turn an idea into a testable rule and backtest it without fooling yourself
- Apply machine-learning models (gradient boosting, regime detection with hidden Markov models) carefully
- Size positions and control risk
- Connect to a broker API and run a strategy in paper trading
Important: this is an educational course. Nothing in it is financial advice or a recommendation to trade. Most trading strategies lose money after costs; test with paper accounts first.
Community and help: every enrolled student gets the course Forum tab — ask the BOSS Pacific team or other students, share fixes and lab results. Read the BP Academy blog for updates and worked examples.
Includes: the full course as a licensed PDF workbook, available after purchase.
Hands-on labs: rent a ready environment from BOSS Pacific — Docker sandbox. Every lab resets every 24 hours and is removed at the end of your rental. Or build your own with the gear listed in the course.