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

  • Basic understanding of AI and machine learning concepts
  • Familiarity with Large Language Models (LLMs)
  • Experience with programming and data handling

Audience

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

Delivery Options

Private Group Training

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  • Delivered online, onsite/classroom or hybrid by experts sharing real world experience

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