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Course Outline

Introduction to LlamaIndex and Context Augmentation

  • Overview of LlamaIndex.
  • The role of context augmentation in AI.
  • Benefits of using LlamaIndex with LLMs.

Setting Up LlamaIndex

  • Installation and configuration.
  • Understanding the architecture and components.
  • Data connectors and ingestion.

Data Indexing and Access

  • Creating data indexes for efficient access.
  • Query engines and natural language access.
  • Best practices for data structuring.

Integrating LlamaIndex with LLMs

  • Enhancing LLMs with contextually relevant data.
  • Practical exercises: Augmenting chatbots and text generators.
  • Troubleshooting and optimization.

Application Scenarios and Case Studies

  • Use cases in various industries.
  • Review of successful implementations.
  • Building a context-augmented AI solution.

Summary and Next Steps

Requirements

  • Fundamental knowledge of AI and machine learning concepts.
  • Familiarity with Large Language Models (LLMs).
  • Experience in programming and data handling.

Audience

  • AI researchers.
  • Machine learning professionals.
  • Data scientists.
 14 Hours

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