Global Certificate in AI Trading Technologies

• Introduction to AI Trading Technologies: Overview of AI in trading, benefits, challenges, and use cases.
• Machine Learning Fundamentals: Supervised, unsupervised, and reinforcement learning, regression, classification, clustering, and dimensionality reduction.
• Deep Learning Techniques: Neural networks, convolutional neural networks, recurrent neural networks, long short-term memory, and gated recurrent units.
• Natural Language Processing: Text preprocessing, sentiment analysis, topic modeling, and named entity recognition.
• Time Series Analysis: Time series components, stationarity, autocorrelation, moving averages, exponential smoothing, and ARIMA models.
• Financial Data Analysis: Data cleaning, feature engineering, descriptive statistics, and visualization.
• Algorithmic Trading Strategies: Market making, statistical arbitrage, trend following, mean reversion, and volatility trading.
• AI Trading Applications: Portfolio optimization, risk management, trade execution, and backtesting.
• Ethical and Regulatory Considerations: Algorithmic bias, transparency, explainability, and regulatory compliance.