This highly-rated course boasts a 4.3-star-star rating from 11 reviews and has successfully guided 138 students in mastering Investing & Trading skills. Featuring 1 hour(s) 30 minute(s) of expert-led content delivered in English, this course offers thorough training to enhance your Social Science expertise. The course details were last updated on December 24, 2024. This coupon code is brought to you by Anonymous.
- Expires on: 2025/07/23
- Last Update: July 18, 2025
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Price:
39.99 $0 $
About This Course
Unlock the power of Artificial Intelligence in the world of trading.
In this hands-on course, you’ll learn how to build, train, and backtest AI-driven algorithmic trading strategies using Python, machine learning, and deep learning tools. Whether you're from finance or tech, this course will help you turn market data into actionable trading signals using LSTM models, sentiment analysis, and advanced evaluation metrics.
You’ll begin with the basics of algorithmic trading, explore the role of AI, and dive deep into tools like Random Forest, Gradient Boosting, CNNs, LSTM, Reinforcement Learning, Genetic Algorithms, and Ensemble Methods. From there, you’ll move into real-world implementation — loading historical stock data, creating predictive features, labeling outcomes, handling class imbalance with focal loss, and evaluating your trading strategy through backtesting and risk metrics like Sharpe Ratio and Drawdown.
This course includes:
Real Apple stock data for hands-on practice
Feature engineering using technical indicators
Custom loss functions like Focal Loss
Building an LSTM model from scratch
Visualizing trading signals and performance
Backtesting with capital growth simulations
By the end, you’ll walk away with a fully functional trading strategy powered by AI — plus the knowledge to apply these techniques across any stock, ETF, or crypto asset.
What You'll Learn
Understand how AI is transforming algorithmic trading
Create predictive trading features from stock data
Train LSTM models to predict buy, sell, or hold signals
Handle imbalanced financial data using oversampling and focal loss
Evaluate trading performance using accuracy, precision, recall, and confusion matrix
Visualize predicted trading signals on real stock charts
Backtest trading strategies using portfolio simulation
Calculate Sharpe Ratio, Drawdown, and Returns for risk analysis
