Alexander Hagmann - Algorithmic Trading A-Z with Python, Machine Learning & AWS (Download)

Did you know that over 75% of retail day traders lose money? The difference between winning and losing traders isn’t luck—it’s data-driven decision-making, rigorous testing, and automation. Most traders rely on intuition or basic technical indicators that everyone else uses, leading to predictable losses. Professional algorithmic trading eliminates emotions, leverages unique strategies, and operates 24/7 with precision that manual trading can’t match.

Course Overview

“Algorithmic Trading A-Z with Python, Machine Learning & AWS” by Alexander Hagmann is the most comprehensive data-driven trading course available. This extensive program teaches you to build, test, and deploy fully automated trading bots using Python, machine learning, and cloud infrastructure. Whether you’re a struggling trader seeking consistency or a data scientist entering finance, this course provides the complete framework for algorithmic trading success.

What You’ll Master

Day Trading Fundamentals with Top Brokers

Understand essential concepts like spreads, pips, margin, leverage, and bid-ask prices across OANDA, Interactive Brokers (IBKR), and FXCM platforms. Learn spot trading versus derivatives, forex and stock trading mechanics, order types and execution strategies, and how to minimize trading costs that destroy most strategies.

Python Programming and Financial Analysis

Build expertise in Python coding with object-oriented programming (OOP), working with Numpy, Pandas, Matplotlib for data analysis, implementing scikit-learn, Keras, and TensorFlow for machine learning, and handling time series financial data effectively.

Technical Indicators and Strategy Development

Code technical indicators from scratch including MACD, ATR, Bollinger Bands, RSI, ADX, and Renko charts. Develop multiple strategy types: SMA crossover systems, momentum and contrarian approaches, mean-reversion strategies, and machine learning-powered regression and classification models.

Rigorous Strategy Testing

Master both vectorized and iterative (event-driven) backtesting techniques, conduct out-of-sample forward testing, measure performance using CAGR, Sharpe ratio, maximum drawdown, and other KPIs, and identify and eliminate look-ahead bias and overfitting.

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Real-Time Implementation and Full Automation

Connect to broker APIs and stream high-frequency tick data, build trader classes that execute strategies in real-time, implement stop-loss and take-profit mechanisms, deploy trading bots on AWS EC2 cloud servers for 24/7 operation, and schedule automated trading sessions with error handling for reliability.

Advanced Topics

Explore deep neural networks (DNN) for predictive trading, sentiment analysis for market direction, value investing with quantitative methods, and multi-strategy combinations for diversification.

Course Structure

With over 400 lectures organized into practical sections, you’ll progress from trading basics through advanced automation. The course includes hands-on coding exercises, role-play scenarios, interactive labs, and real-world implementation with live brokers.

Who Should Enroll

This course is perfect for day traders wanting to professionalize and automate their approach, investors tired of losing money with hope-based strategies, finance professionals transitioning to data-driven methods, and data scientists applying machine learning to financial markets.