Artificial intelligence is reshaping financial markets, but the promise of effortless AI trading profits is a dangerous myth. This book cuts through the hype to give you a realistic, step-by-step framework for designing, testing, and deploying automated trading systems that actually respect risk. You'll learn how machine learning models process market data, why backtesting can deceive you, and how to avoid the common pitfalls that wipe out beginners. From understanding order types and slippage to building a simple trend-following bot in Python, every chapter builds practical skills without promising quick riches. We explore the limits of AI—overfitting, regime changes, and liquidity risks—and show you how to think like a quant rather than a gambler. Whether you're a curious coder or a trader exploring automation, this blueprint gives you the honest foundation you need. No get-rich-quick schemes, no guaranteed returns—just the real mechanics of algorithmic trading and the discipline to survive long enough to improve. Part of The AI Trading Library.