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AI Agent Development

AI Agent with LangGraph version 1 From Basics to Advanced

This course covers the entire process of evolving ChatGPT from a simple conversational AI to an intelligent AI Agent that performs actual work tasks. Using three core frameworks - LangChain, LangGraph, and LangSmith - you'll directly create AI Agents that can be immediately used in real-world applications.

35 learners are taking this course

  • goodwon5937125
AI 활용법
AI 코딩
langchain
langgraph
langsmith
AI
ChatGPT
LLM
Generative AI
AI Agent

What you will gain after the course

  • How to Utilize LLM with LangChain

  • How to Use AI Agents with LangGraph

  • AI (LLM) Monitoring Using LangSmith

  • AI Agent Service Integrated with RDB

Building Practical AI Agents with the Latest LangGraph v1

Master the core technology of the AI era, AI Agent, step by step!

  • This covers the entire process of ChatGPT evolving from a simple conversational AI to an intelligent AI Agent that performs actual work tasks.

  • Using the three core frameworks LangChain, LangGraph, and LangSmith, you'll build AI Agents that can be used immediately in real-world applications.

I recommend this for people like this

Job seekers

Someone who wants to add AI Agent development skills to their portfolio

AI/Backend Developer

Developers who want to create AI Agents that can be used in real work beyond the ChatGPT API

AI Planner/PM

AI Agent technology understanding and project application for planners

Expected Benefits After Taking the Course

  • AI Agent Development Capabilities

    • Beyond simple conversational chatbots, it's possible to develop AI Agents that perform actual work tasks

  • Production deployment capability

    • Securing practical service operation capabilities through monitoring and evaluation using LangSmith

  • Complex Workflow Design

    • Designing and Implementing Multi-Step Agent Systems with LangGraph

  • Data Integration Capability

    • Database, web search, and other external system integration practical skills

Features of this course

studio

Advanced Workflow Design

  • Designing Complex Agent Workflows Based on LangGraph

  • Handling Dynamic Branching with Conditional Edges

  • Visual development and debugging with LangGraph Studio

Production Level Operations

  • LangSmith Integration

    • Debugging and Performance Analysis with Execution Tracing

    • Dataset Construction and Model Performance Improvement through Automated Evaluation

  • Memory Management

    • Building an intelligent memory system with conversation history, summaries, and encrypted storage

You'll learn this kind of content

From Basics to Practice - Step-by-Step Learning Structure

  • How to Use Models: OpenAI, Groq, Ollama, Huggingface, etc.

  • Prompt Engineering: PromptTemplate, FewShot, etc.

  • Output Parsing: Str, CSV, JSON, etc.

  • Mastering LCEL: Building Complex Workflows with Parallel Chains, Conditional Branching, Batch Processing, Streaming, and More

LCEL (LangChain Expression Language)

Building Practical AI Agents

  • Tools & Agents: Integration with real tools such as web search, graph generation, database queries, etc.

  • SQL Agent Development: Intelligent query agent that integrates with databases such as SQLite, MySQL, PostgreSQL

  • ReAct Pattern: Implementing Complex Problem-Solving Capabilities Through Reasoning + Acting

ReAct Agent

Pre-enrollment Reference Information

Practice Environment

  • The course was recorded in a MacOS environment, but it is also possible on Windows and Linux.

  • The course uses the VSCode editor, but it's possible with all editors such as Cursor, PyCharm, etc.

Learning Materials

  • Compressed files (requirements.txt, jupyter files, etc.) are provided for each section.

Prerequisites and Important Notes

  • Python

Recommended for
these people

Who is this course right for?

  • General public or students interested in AI or LLM

  • A developer interested in developing chatbot services using LLM

  • Developers who want to build business services using LangChain & LangGraph

Need to know before starting?

  • I need basic knowledge about Python.

  • (Optional) Basic knowledge of RDB (MySQL or PostgreSQL, etc.) is required.

  • (Optional) It would be helpful to have basic knowledge of Docker.

  • (Optional) It would be good to have basic knowledge about Hugging Face.

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5

Reviews

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Answers

4.6

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안녕하세요, 강의를 맡은 조경원입니다.
저는 중소기업부터 대기업까지 다양한 산업 환경에서 웹 개발, 인공지능(AI), 그리고 AWS 인프라 구축 등 폭넓은 실무 경험을 쌓아왔습니다.

이러한 경험을 바탕으로 2022년부터는 오프라인에서 AI 분야의 강의를 진행하며, 실무와 이론을 연결하는 교육을 이어오고 있습니다.

Curriculum

All

51 lectures ∙ (7hr 55min)

Course Materials:

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