Developing RAG Applications

2

Days

Online Live

Delivery Method

Specialty

Skill Level

$1,200 USD

Fee

Overview

This course offers a comprehensive understanding of key Retriever-Augmented Generation (RAG) concepts, techniques, and application strategies for building LLM-powered applications. It’s designed for both LLM Engineers and AI Developers looking to advance their skills in developing RAG-based LLM solutions. Participants will gain hands-on experience in building RAG applications, working with vector databases, document ingestion and indexing, document ranking, and generating outputs using LangChain.

Completing this course will help you:

  • Gain a deep understanding of RAG concepts and applications.
  • Configure and manage vector databases such as Chroma and Milvus.
  • Develop RAG-powered applications using Python, LangChain, and FastAPI or Streamlit.
  • Understand advanced RAG techniques to improve performance.

Curriculum

  • Module 1 - RAG Introduction
    • Understand the fundamentals of RAG.
    • Explore how RAG can help address the shortcomings of LLMs such as hallucination.
    • Learn the key benefits of integrating RAG techniques in applications.
  • Module 2 - Vector DB Introduction
  • Module 3 - LangChain and LlamaIndex
  • Module 4: RAG Evaluation
  • Module 5 - Mini RAG Application Project

Schedule

Online

Jan 09 - 10, 2025

9:30am - 4:30pm EST

Online

Mar, 2025

9:30am - 4:30pm EST

Online

Jul, 2025

9:30am - 4:30pm EDT

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