The lecture is well-prepared.
However, it would be even better if it could lead to an actual service.

dachki

This course is a practice-oriented lecture that goes beyond
👉 just explaining the concepts of RAG (Retrieval-Augmented Generation),
👉 to building the actual working architecture yourself,
👉 and experiencing expansion and optimization.

Starting from simple RAG examples, you will learn step-by-step—from Advanced RAG to Modular RAG and Agent-based RAG—at a level that can be immediately applied in the field.

goodwon5937125

Agentic (Modular) RAG with LangGraph Version 1: From Basics to Advanced

실습 중심

ai in practice

AI 활용법

LangGraph

langgraph

multi-agent

rag시스템구축

입문

초급

중급이상

챗지피티

ChatGPT

prompt engineering

대규모 언어 모델

Orientation

Naive RAG > Loader

Naive RAG > PDF Loader

Naive RAG > Splitter

Naive RAG > Embedding Models

Naive RAG > VectorDB

Naive RAG > RAG

# Advanced RAG > VectorDB

# Advanced RAG > Retriever

Advanced RAG > RAG

# Advanced RAG > Evaluation

Agentic (Modular) RAG