framework
  • News
62k
  • Start Here: Welcome to the Bootcamp
  • Module 1: Basics of LLMs
  • Module 2: Word Vectors, Simplified
  • Module 3: Prompt Engineering and Token Limits
  • Module 4: RAG and LLM Architecture
    • What is Retrieval Augmented Generation (RAG)?
    • Basic RAG Architecture with Key Components
    • RAG versus Fine-Tuning and Prompt Engineering
    • Versatility and Efficiency in RAG
    • Key Benefits of using RAG in an Enterprise/Production Setup
    • Implementation of RAG for Production Use Cases
    • 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
    • Graded Quiz 2
  • Module 5: Hands-on Development
  • Module 6: Project Tracks and Submission
  • GitHub0k

Bonus Video: Implementing End-to-End RAG | 1-Hour Session

Now that you've understood what RAG is, below is a 1-hour video where Mudit from Pathway hosts Jayprasad Hegde, Head of Data Science at the National Payments Corporation of India (NPCI). This session covers a brief introduction of co-hosts followed by a presentation that covers the full spectrum of RAG: from hardware considerations to actual RAG application.

Module 4 Rag And Llm Architecture

Using kNN and LSH to Enhance Similarity Search (Bonus Module)

Module 4 Rag And Llm Architecture

Graded Quiz 2

  • 62k
Product
  • Pathway Framework
  • RAG Templates
  • Why Pathway?
  • Pricing
  • Get Free Enterprise Features
  • Pathway Templates
Resources
  • Developer Docs
  • Success Stories
  • Bootcamps
  • Blog
  • Events
Company
  • Careers
  • Newsroom
  • Media kit
  • Licensing Terms
  • Policies
Contact
  • Chat with us on Discord
  • Pathway
  • 418 Florence Street
  • Palo Alto, CA 94301
© 2021-2025 Pathway