Course Outline

Introduction to Large Language Models in Finance for Government

  • The Role of Artificial Intelligence and Large Language Models (LLMs) in Financial Analysis for Government
  • Overview of LLMs and Their Capabilities in Text Analysis for Government
  • Case Studies: Application of LLMs in Financial Forecasting and Risk Assessment for Government

Utilizing LLMs for Financial Data Processing for Government

  • Extracting Financial Indicators from Unstructured Data Using LLMs for Government
  • Training LLMs on Financial Texts for Sentiment Analysis for Government
  • Correlating News Sentiment with Market Movements for Government

Building Predictive Models with LLMs for Government

  • Designing LLM-Based Models for Stock Price Prediction for Government
  • Forecasting Economic Trends Using LLM-Generated Insights for Government
  • Backtesting Models with Historical Financial Data for Government

Integrating LLMs into Investment Strategies for Government

  • Incorporating LLM Analytics into Quantitative Trading for Government
  • LLMs for Portfolio Optimization and Risk Management for Government
  • Communicating AI-Driven Insights to Stakeholders for Government

Hands-on Lab: Financial Market Prediction Project for Government

  • Setting Up a Financial Data Analysis Environment with LLMs for Government
  • Developing a Market Prediction Model Using LLMs for Government
  • Evaluating Model Performance and Making Improvements for Government

Summary and Next Steps for Government

Requirements

  • A foundational knowledge of financial markets and instruments for government applications.
  • Experience with Python programming and data analysis techniques.
  • Familiarity with machine learning concepts and statistical models for government use.

Audience

  • Financial analysts in the public sector
  • Data scientists working for government agencies
  • Investment professionals serving governmental organizations
 14 Hours

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