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LLM Course
Ctrlk
  • Welcome to the Bootcamp
  • Basics of LLMs
  • Word Vectors, Simplified
  • Prompt Engineering and Token Limits
  • RAG and LLM Architecture
    • Basics of RAG
      • What is Retrieval Augmented Generation
      • Primer to RAG: Pre-trained and Fine-Tuned LLMs
      • In-context Learning
      • LLM Architecture Components for In-context Learning
      • LLM Architecture Components
    • RAG Architecture Diagram
    • RAG versus Fine-Tuning and Prompt Engineering
    • Versatility and Efficiency in RAG
    • Key Benefits of using RAG in an Enterprise/Production Setup
    • Hands-on Demo: Performing Similarity Search in Vectors (Bonus Module)
    • Using kNN and LSH to Enhance Similarity Search (Bonus Module)
    • Bonus Video: Implementing End-to-End RAG | 1-Hour Session
    • Graded Quiz 2
  • Hands-on Development
  • Final Project + Giveaways
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  1. RAG and LLM Architecture
  2. Basics of RAG

What is Retrieval Augmented Generation

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