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Duration 14 hours
Course Outline
Introduction to LLMs in Finance
- The impact of AI and LLMs on financial analysis
- A comprehensive overview of LLM capabilities in text analysis
- Case studies illustrating LLMs in financial forecasting and risk assessment
Processing Financial Data with LLMs
- Extracting key financial indicators from unstructured data using LLMs
- Adapting LLMs for sentiment analysis on financial texts
- Analyzing the correlation between news sentiment and market fluctuations
Constructing Predictive Models with LLMs
- Architecting LLM-based models for stock price forecasting
- Predicting economic trends by leveraging LLM-generated insights
- Validating models through backtesting with historical financial data
Embedding LLMs in Investment Strategies
- Merging LLM analytics into quantitative trading frameworks
- Applying 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 utilizing LLMs
- Building a market prediction model with LLM support
- Assessing model performance and implementing iterative improvements
Requirements
- Fundamental knowledge of financial markets and instruments
- Proficiency in Python programming and data analytics
- Working familiarity with machine learning principles and statistical modeling
Target Audience
- Financial Analysts
- Data Scientists
- Investment Professionals
