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Course Outline
Introduction to LLMs in Finance
- The role of AI and LLMs in modern financial analysis
- An overview of LLM capabilities in text analysis
- Case studies: Applying LLMs to financial forecasting and risk assessment
Processing Financial Data with LLMs
- Extracting key financial indicators from unstructured data using LLMs
- Training LLMs on financial texts for accurate sentiment analysis
- Correlating news sentiment with market movements
Constructing Predictive Models with LLMs
- Designing LLM-based models for stock price prediction
- Forecasting economic trends using insights generated by LLMs
- Backtesting models against historical financial data
Integrating LLMs into Investment Strategies
- Incorporating LLM analytics into quantitative trading strategies
- Utilizing LLMs for portfolio optimization and risk management
- Communicating AI-driven insights effectively to stakeholders
Hands-on Lab: Financial Market Prediction Project
- Setting up a financial data analysis environment utilizing LLMs
- Developing a market prediction model powered by LLMs
- Evaluating model performance and implementing improvements
Requirements
- A foundational understanding of financial markets and instruments
- Proficiency in Python programming and data analysis
- Working knowledge of machine learning concepts and statistical modelling
Target Audience
- Financial analysts
- Data scientists
- Investment professionals
14 Hours
