Bridging the gap between learning and execution, this course focuses on implementing real-world algorithmic trading projects. It’s a practical guide to creating, testing, and deploying full-fledged trading systems based on real market data. The course begins with project planning—choosing a strategy type (momentum, mean reversion, breakout), sourcing data, and setting success criteria. You’ll then build several complete projects: for example, a moving average crossover strategy on equities, an intraday volatility-based system on BankNifty, or an RSI-based signal bot for crypto. Each project involves data collection, signal generation, position sizing, backtesting, and result interpretation. You'll also learn to set up monitoring, logs, and notifications using Telegram or email alerts. Deployment strategies include local servers and cloud-based environments. Emphasis is placed on risk control, slippage modeling, and optimizing for live environments. This course is a must for those who’ve learned the theory of algo trading and want to bring it into practice with tangible output.