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AI Agent Development

Complete AI Agent Development All-in-One (w. LangGraph, Google ADK, CrewAI)

From work productivity to monetization, we'll teach you everything about AI agent development that you can apply directly to real-world tasks. Become an "AI Agent Development Expert" by directly developing 7 agents based on technologies including n8n, CrewAI, LangGraph, Google ADK, multi-agent orchestration, RAG, multimodal, MCP, A2A, and more.

(4.9) 29 reviews

573 learners

  • amamov
실습 중심
AI 코딩
Python

Reviews from Early Learners

What you will learn!

  • Development of AI automation architecture for sophisticated complex systems beyond simple automation

  • From work productivity to monetization, everything about AI agent development that can be immediately applied in practice

  • CrewAI, LangGraph, Google ADK, multi-agent orchestration, RAG, multimodal, and other AI Agents technologies

"Multi AI Agent Development" for immediate practical use,
Lead the Software 3.0 era 🤖


Are you satisfied with simply asking questions to ChatGPT? 🤔

Single AI systems like ChatGPT have limitations. Truly effective AI systems in practice are multi-agent systems where multiple expert AIs collaborate.

Now is the era where AI analyzes news, develops investment strategies, and writes blog posts on your behalf. It operates just like a real company where researchers gather information, analysts interpret data, and managers make final decisions.

Imagine this: receiving personalized news briefings every morning, having an AI fund manager automate your stock investments, and SEO-optimized blog posts completing themselves automatically... This is the reality of the Software 3.0 era where multi-agents collaborate.



From work productivity to monetization, we'll teach you everything about
multi-AI agent development that you can apply directly to your work


In this course, you will directly develop 7 advanced AI agents using the latest frameworks proven in practice, including CrewAI, LangGraph, Google ADK, n8n, and more.

In particular, you can learn how to apply the latest AI technologies such as multi-agent orchestration, RAG, and multimodal processing in practice, and master systematic development processes from prompt engineering to TDD methodology.




4 Core Frameworks

n8n

Learn the basic concepts of agents while automating workflows without coding.

LangGraph

Develop flexible basic agents with state-based cyclic graph structures. Learn concepts about Flow and State.



CrewAI (Role-based Multi-Agent System)

Learn how to build and collaborate role-based autonomous agent teams (A2A), and complete complex
multi-agent systems.

Google ADK (Agent Development Kit)

Develop hierarchical advanced agents with Google's latest agent development kit.




7 Practical Agent Projects


🤖 AI Chatbot Agent - ChatGPT Clone Development (Basic Single Agent)

📰 News Briefing Agent - Your Personal News Reporter Every Morning

📈 Stock Investment Automation Agent - My Own AI Fund Manager

📝 Blog Content Agent - SEO Optimization Automated Content Manager

🎧 English Conversation Tutor Agent - Voice and RAG-based Learning System

🎨 Media Studio Agent - Image/Video Generation and Editing

📱 YouTube Shorts Production Agent - Agent & Sub-agent Collaboration, Fully Automated Video Production System




Core Technologies for Building Agent Systems


Agent, Task, Tool Definition and Design

For agents to go beyond simple calls, clear role definition and expertise design are necessary. You will learn how to define personas and expertise, write clear task specifications, and develop and integrate various tools such as web search, data analysis, and API integration.

Dynamic Memory System

Memory is a core capability of agents that enables understanding context and providing personalized responses. By implementing Short-term Memory and Long-term Memory systems, we can give agents the ability to learn and remember.

Multi-Agent Orchestration(A2A)

For multiple agents to collaborate, orchestration technology that coordinates the flow must be supported. Through real-world examples such as the researcher-writer-editor collaboration of news briefing agents and the analyst-manager collaboration of stock investment agents, we design agent cooperation systems.

Agent Communication Protocols

Collaboration rules such as message passing between agents, state synchronization, and task distribution mechanisms must be established for agents to work together smoothly. We implement various collaboration patterns from sequential execution to parallel processing and conditional routing, and design task distribution mechanisms between agents.

RAG, Context-aware Retrieval

We develop a RAG system that understands the intent of questions and selectively searches for highly relevant information. We conduct hands-on practice creating a customized English conversation tutor by training it with PDF English textbooks.

Multi-modal Integration

We develop multimodal agents that go beyond text to handle voice recognition/synthesis, image generation/editing, and video production.




💡 This is different from lectures that only teach how to use frameworks 💡

It goes beyond simply connecting APIs and following examples. It systematically covers in-depth practical skills needed to grow into a true AI agent developer, including designing collaboration mechanisms between agents, dynamic memory management, and implementing complex workflows.


Features of this course

  • Development of 7 Complete Production-Ready AI Agents - Build sophisticated agents from start to finish that can be immediately applied to real work, not just simple demos. From news briefings to investment automation and content generation, each operates as an independent business solution.

  • Everything About Multi-Agent Orchestration - Design systems where multiple specialized AIs collaborate rather than a single AI. Implement actual team structures with AI, such as investment bots where researcher-analyst-manager cooperate, and content bots where writer-editor-SEO specialist work as a team.

  • Developing a True Personal Assistant-Level AI Agent - AI Agent evolving with Memory & RAG, implementing AI that remembers and learns beyond simply responding. From Firebase-based long-term memory, PDF document learning, to personalized responses - develop a true personal assistant-level AI agent.

  • Step-by-step learning design that transforms beginners into experts - First, get a feel for what agents are using the n8n no-code tool, then gradually build full-scale systems with Python. It's okay if you have little coding experience. We'll explain everything step by step, while ensuring the final result is at a level you can actually use in practice.

  • Complete Mastery of AI Frameworks - Master key tools used in the field such as CrewAI, Google ADK, and more.

  • 90% Hands-on Practice, 10% Theory - Build real-world development experience by writing and testing all code directly.


"In the future, every company's IT department will
serve as the HR department for AI agents"

- Jensen Huang




I recommend this for people like this

Aspiring AI Agent Developer (AI Engineer)
Those who want to go beyond simple AI utilization
to develop full-scale agent systems / Students

Office workers interested in work automation.
Those who want to replace repetitive tasks with AI
and maximize productivity

Those preparing to start an AI startup
Those planning to develop innovative services or
products based on AI agents

Those interested in complex automation systems
Those who want to implement workflow automation that requires
advanced decision-making and collaboration, not simple repetition

After taking the course

  • You will be able to freely handle multi-agent architecture design and A2A technology.


  • You will become proficient in handling AI agent frameworks such as CrewAI, Google ADK, LangGraph, etc.

  • You will be able to integrate RAG and multimodal AI into complex agent systems


  • You will be able to develop advanced agents that include dynamic memory and state management.


  • 7 Complete AI Agent Portfolios that can be customized to your personal situation and immediately applied to real work.

Recommended for
these people

Who is this course right for?

  • Aspiring AI Agent Developer for Adapting to the Software 3.0 Era

  • Office workers interested in work automation, those interested in complex automation systems

  • Those preparing AI startup ventures or solo business monetization models

Need to know before starting?

  • Basic Python syntax (def, class, decorator, async, await, ...)

Hello
This is

5,973

Learners

317

Reviews

362

Answers

4.8

Rating

4

Courses

안녕하세요. 더 유익하고 본질적인 지식 콘텐츠로 많은 가치를 드릴 수 있도록 노력하겠습니다.

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Curriculum

All

48 lectures ∙ (10hr 39min)

Course Materials:

Lecture resources
Published: 
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Reviews

All

29 reviews

4.9

29 reviews

  • candy53362500님의 프로필 이미지
    candy53362500

    Reviews 2

    Average Rating 5.0

    Edited

    5

    69% enrolled

    とてもKindに上手く教えてくださいます。反復的な業務を会社で自動化しようと以前にn8nで単純にワークフローを作ってやってみたのですが、正直...現実的に複雑な業務に適用するのがとても不便だったのですが、この講義で以前作ったものをコードベースでエージェントを再開発しているのですが、とても良いですね。コードでやるとAIがプロンプトやワークフローも組んでくれてとても良いです。早く次にオープンされるセクション講義が待ち遠しいですね...エージェント講義の中で一番だと思います。

    • nareya99953212님의 프로필 이미지
      nareya99953212

      Reviews 1

      Average Rating 5.0

      5

      88% enrolled

      現在までオープンされたセクションだけでも十分に価値があります。エージェント開発の基礎から着実に学んでいるのですが、とても良いです。10月に残りのセクションがオープンされれば、より深い内容を学べそうで期待しています。先生、お体にお気をつけください。

      • blessthy님의 프로필 이미지
        blessthy

        Reviews 13

        Average Rating 5.0

        5

        75% enrolled

        現在オープンされている講義は全て見て受講評を残します。私はN8Nに触れてからこれが二番目に触れるAI講義なのですが、N8NからLangGraphまで簡単に概観してその後CrewAIに入って頂いたおかげでLangGraphも軽く概観することができて良かったです。途中でプロンプトエンジニアリングセクションもよく聞きました。全てを説明することはできないので深みはないと思われますが、最大限多くのことをあちこちによく織り込んで説明してくださっています。CrewAIが何なのか分からない初めて触れる人の目線に合った良い講義でした。残りのオープン予定の講義も期待しています。ありがとうございます〜

        • oneoff님의 프로필 이미지
          oneoff

          Reviews 2

          Average Rating 5.0

          Edited

          5

          72% enrolled

          n8n → langgraph → crewaiと続くカリキュラムがかなり自然で、満足しています。 すべてのエージェントフレームワークを一度ずつ使ってみて、crewaiが結局一番良いということを感じました。 crewaiを使ってほとんどのプロジェクトを行うのですが、一つのagentを使用する簡単なプロジェクトから、multi-agentとflowを組み合わせた複雑なプロジェクトまで段階的に学べる方式なので、とても良いです。 toolやmemoryもライブラリで提供されているものを単純に持ってきて使うよりも、customで開発する方法を教えてくださるので、私が持っているagentアイデアをコード化するのに大きな助けになりました。

          • djc060132164님의 프로필 이미지
            djc060132164

            Reviews 1

            Average Rating 5.0

            5

            97% enrolled

            AI エージェント講義の中で最も実務に直接的に役立つ講義だと思います。分かりやすく説明してくださり、一歩一歩教えてくださったおかげで疲れることなく完走することができました。これから残りのセッションもしっかりついていきます😆😆 やはり受講生が多い講師の講義には理由がありますね〜!! みなさん悩まずにゴーゴーしましょう 一緒に受講しましょう

            $64.90

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