LlamaIndex: Enhancing Contextual AI Training Course
LlamaIndex is an open-source data framework built for applications leveraging Large Language Models (LLMs) that benefit from context augmentation. It is particularly effective for systems utilizing Retrieval-Augmented Generation (RAG) architectures.
This instructor-led live training, available online or onsite, targets intermediate-level AI researchers, machine learning practitioners, and data scientists who want to utilize LlamaIndex to boost the accuracy and reliability of their AI models across various applications.
Upon completing this training, participants will be able to:
- Grasp the core principles and components of LlamaIndex.
- Ingest and structure data for integration with LLMs.
- Apply context augmentation techniques to enhance AI model performance.
- Incorporate LlamaIndex into existing AI systems and workflows.
Course Format
- Interactive lectures and discussions.
- Extensive exercises and practical practice.
- Hands-on implementation in a live-lab environment.
Customization Options
- To request customized training for this course, please contact us to make arrangements.
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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 in various industries
- Review of successful implementations
- Building a context-augmented AI solution
Summary and Next Steps
Requirements
- Basic knowledge of AI and machine learning concepts
- Familiarity with Large Language Models (LLMs)
- Experience in programming and data handling
Target Audience
- AI researchers
- Machine learning professionals
- Data scientists
Open Training Courses require 5+ participants.
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Provisional Upcoming Courses (Require 5+ participants)
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