Quant trading combines mathematics, data science, and automation to make trading decisions—but contrary to hype, it is not a guaranteed path to riches. This book strips away the myths and gives you an honest, step-by-step guide to understanding how quantitative strategies work, how artificial intelligence fits into them, and what it takes to build your own systems. From sourcing clean data and building simple backtests to learning the limits of machine learning in markets, you will gain a realistic foundation. Each chapter emphasizes genuine risk: most algorithmic traders lose money, leverage multiplies losses, and past performance never predicts the future. You will learn why AI cannot 'beat the market' reliably and how to spot overhyped trading bots. Whether you are a hobbyist or considering a career, this book helps you think like a quant without falling for promises of easy profits. Practical exercises and risk check boxes keep you grounded. Part of The AI Trading Library.