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
Requirements
- Basic knowledge of Python programming
- Familiarity with Pandas, NumPy, and Matplotlib
- No prior experience with deep learning or stock trading is required — LSTM and trading concepts are introduced step-by-step
- Some exposure to machine learning will help in understanding the LSTM-based models more easily
Who This Course is For
- Aspiring algorithmic traders looking to build AI-powered strategies
- Data scientists and ML engineers interested in finance and trading
- Quantitative analysts and fintech professionals exploring automation
- Students and researchers in finance, statistics, or computer science
- Anyone curious about LSTM, NLP, and deep learning for real-time trading
Your Instructor
Learnsector LLP
Learn to Win
4.4 Instructor Rating
20,513 Reviews
465,486 Students
33 Courses
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