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You use ChatGPT, but haven't you found it difficult to explain why it gives certain answers?

"I know terms like RAG, Agents, and Fine-tuning... but it's hard to explain them accurately."

"I get tongue-tied whenever I hear LLM-related terminology."

"Conceptual explanations are always vague during AI meetings."

This course was created specifically for people like you.

This is a theoretical course designed to help you understand LLMs not just as a 'tool,' but as a 'structure.'
It doesn't teach you how to use ChatGPT or Gemini; instead, it establishes the foundation so you can explain exactly why they work the way they do.

leejinkyu0612

Understanding Core LLM Theories through Structure: The Working Principles of ChatGPT, RAG, and Agents All at Once

llm활용

맞춤형llm

llm성능평가및튜닝

llm이론

HappyAI

입문

초급

중급이상

챗지피티

ChatGPT

prompt engineering

대규모 언어 모델

검색증강생성

AI 에이전트

AI Agent

Lecture 1. Basic Understanding of Generative AI and LLM

LLM Trends and Industry Developments

Basics of how LLMs work

Prompt Engineering Theory

RAG, supplementing the limitations of LLM

Understanding and Improving RAG Performance

Fine-tuning & Efficient Tuning Strategies

Understanding and Utilizing LLM Agents

Latest Theories on MCP and A2A