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Duration 14 hours
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 across various industries.
- Review of successful implementations.
- Building a context-augmented AI solution.
Summary and Next Steps
Requirements
- Foundational knowledge of AI and machine learning concepts.
- Familiarity with Large Language Models (LLMs).
- Proficiency in programming and data management.
Target Audience
- AI researchers.
- Machine learning engineers.
- Data scientists.
