Course Outline

Introduction to LlamaIndex and Context Augmentation for Government

  • Overview of LlamaIndex
  • The role of context augmentation in artificial intelligence (AI) for government
  • Benefits of using LlamaIndex with language models (LLMs) for government applications

Setting Up LlamaIndex for Government Use

  • Installation and configuration procedures for government systems
  • Understanding the architecture and components of LlamaIndex for government
  • Data connectors and ingestion methods suitable for government data sources

Data Indexing and Access for Government Operations

  • Creating data indexes to facilitate efficient access for government use
  • Query engines and natural language access tailored for government datasets
  • Best practices for structuring government data for optimal performance

Integrating LlamaIndex with LLMs for Government Applications

  • Enhancing LLMs with contextually relevant government data
  • Practical exercises: Augmenting chatbots and text generators for government services
  • Troubleshooting and optimization techniques for government systems

Application Scenarios and Case Studies for Government

  • Use cases in various government sectors
  • Review of successful implementations within the public sector
  • Building a context-augmented AI solution for government operations

Summary and Next Steps for Government Implementation

Requirements

  • A foundational understanding of artificial intelligence and machine learning concepts for government applications.
  • Familiarity with Large Language Models (LLMs) and their potential uses in public sector projects.
  • Practical experience with programming and data handling, particularly in a governmental context.

Audience for Government

  • AI researchers working on government initiatives
  • Machine learning professionals engaged in public sector projects
  • Data scientists supporting governmental data-driven initiatives
 14 Hours

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