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AI Agent Development

High-Quality AI Agent Context Engineering

Learn context engineering techniques for creating high-quality AI agents through hands-on practice.

6 learners are taking this course

  • AISchool
실습 중심
ai에이전트개발
llm
langgraph
ai활용
AI Agent
LangGraph
AI
Generative AI
openAI API

What you will learn!

  • High-Quality AI Agent Development Context Engineering Techniques

  • The Concept and Implementation Methods of Context Engineering

  • How to Implement High-Quality AI Agents Using LangGraph

  • Use Cases of AI Agents

  • How to Implement AI Agents Using Generative AI

Essential skills for AI developers to create high-quality AI agents: Context Engineering!

Learn Context Engineering techniques for creating high-quality AI agents through hands-on practice.

  • How to store and retrieve information using Memory

  • How to Design Optimal Prompts and Effectively Connect Them to Create High-Quality AI Agents


I recommend this for people like this

High-quality AI agents

Those who want to create

Those who want to go beyond implementing simple AI agents and create high-quality AI agents

LangGraph implementation skills

Those who want to improve

Those who want to improve their ability to implement complex agents using LangGraph

The latest AI trends

Those who don't want to miss out

Those who don't want to miss the latest AI trends including Context Engineering

Prerequisites✅

👋 This course is a course that requires prerequisite knowledge of Python, Natural Language Processing (NLP), LLM, LangChain, and LangGraph. Please make sure to take the courses below first or have equivalent knowledge before taking this course.

Large Language Models (LLM) for Everyone Part 5 - Building Your Own AI Agent with LangGraph

Q&A 💬

Q. What is Context Engineering?

Context Engineering is building a dynamic system that provides the right information and tools in the right format so that LLMs can reasonably accomplish tasks.

Q. Why is context engineering important for creating high-quality AI agents?

With the significant improvement in LLM performance, now the key to whether problems are solved or not has become a matter of how suitable context is provided to the LLM, rather than the LLM's performance itself.

Additionally, as various methodologies and tools for building AI agent systems have emerged, an environment has been created where appropriate context can be effectively delivered to LLMs through diverse methods.

Therefore, context engineering has become one of the most important skills for AI developers.


Q. Is prior knowledge required?

This [Context Engineering for Building High-Quality AI Agents] course covers project practice implementing AI agents using the LangGraph library and LLM. Therefore, the course proceeds under the assumption that you have basic knowledge of Python, natural language processing, LLM, LangChain, and LangGraph. If you lack the prerequisite knowledge, please make sure to take the prerequisite course [Large Language Models LLM for Everyone Part 5 - Building Your Own AI Agent with LangGraph] first.

Recommended for
these people

Who is this course right for?

  • Those who want to create high-quality AI agents

  • Those who want to create their own AI agent with LangGraph

  • Those who want to conduct research related to artificial intelligence/deep learning

  • Someone who is preparing for an AI (Artificial Intelligence) graduate program

Need to know before starting?

  • Python usage experience

  • Experience taking the prerequisite course [Large Language Models LLM for Everyone Part 5 - Building My Own AI Agent with LangGraph]

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Answers

4.6

Rating

30

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Curriculum

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30 lectures ∙ (6hr 46min)

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