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Duration 14 hours
Course Outline
Introduction to LLMs in Finance
- The impact of AI and LLMs on financial analysis
- Overview of LLM capabilities in text analysis
- Case studies: Applying LLMs to financial forecasting and risk assessment
LLMs for Financial Data Processing
- Extracting key financial indicators from unstructured data using LLMs
- Training LLMs on financial texts for advanced sentiment analysis
- Analyzing the correlation between news sentiment and market movements
Building Predictive Models with LLMs
- Architecting LLM-based models for stock price prediction
- Forecasting economic trends through LLM-generated insights
- Backtesting models against historical financial datasets
Integrating LLMs into Investment Strategies
- Embedding LLM analytics into quantitative trading strategies
- Using LLMs for portfolio optimization and risk management
- Effectively communicating AI-driven insights to stakeholders
Hands-on Lab: Financial Market Prediction Project
- Configuring a financial data analysis environment with LLMs
- Developing a functional market prediction model using LLMs
- Evaluating model performance and implementing refinements
Requirements
- Foundational knowledge of financial markets and instruments
- Proficiency in Python programming and data analysis techniques
- Working understanding of machine learning principles and statistical modeling
Target Audience
- Financial analysts
- Data scientists
- Investment professionals
