Algorithmic Trading with AI Agents and Dual Moving Averages

Algorithmic trading enables disciplined, data-driven financial decision-making without emotional bias. In this text-based course, you will learn how to design automated trading logic using dual moving average crossovers and enhance strategy execution with AI agents. You will gain a solid understanding of quantitative market mechanics, technical indicators, and automated agent design. Through structured reading, code walkthroughs, and practical exercises, you will transition from core market principles to building tested trading rules. What you'll learn: - Understand core quantitative finance terminology, market indicators, and moving average fundamentals - Implement fast and slow simple and exponential moving average crossover calculations in Python - Design AI-assisted agent logic to evaluate signals, manage orders, and control portfolio exposure - Backtest dual moving average trading strategies against historical price datasets - Apply robust risk management rules including stop-loss levels and position sizing limits - Evaluate strategy performance using modern risk-adjusted metrics like Sharpe ratio and maximum drawdown The course begins with foundational financial definitions and indicator mathematics before guiding you step by step through strategy scripting, backtesting, and AI agent integration. Designed specifically for beginners, this course requires no prior trading or machine learning background. Start reading today to build your own algorithmic trading strategies.