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AI Agent Development

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

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

78 learners are taking this course

  • amamov
실습 중심
AI 코딩
Python

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.

Especially, 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'll 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. Implement Short-term Memory and Long-term Memory systems to 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. We design agent collaboration systems through real-world examples such as the researcher-writer-editor collaboration of news briefing agents and the analyst-manager collaboration of stock investment agents.

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 courses 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 functions 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 researchers-analysts-managers cooperate, and content bots where writers-editors-SEO specialists work as a team.

  • Developing a True Personal Assistant-Level AI Agent - AI Agent Evolving with Memory & RAG, implementing AI that goes beyond simple responses to remember and learn. 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 turns 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 business automation that requires
advanced decision-making and collaboration, not simple repetition

After taking the course

  • You will be able to freely master 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 in real-world work.

This course is a serialized course, and the series will be completed by the end of October.
~10/20 : Early Bird Discount 60% !!!

  • Section 5 : Opens October 3rd

  • Sections 6, 7 : Opens October 17th

  • Section 8 : Opens October 24th

From November onwards, we plan to open supplementary lectures for each section and additional supplementary sections sequentially as needed.
(The supplementary sections below may be partially modified during the planning process.)
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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

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Learners

271

Reviews

337

Answers

4.7

Rating

4

Courses

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문의사항, 추가질문, 집필, 강의제안 ==> endupfree@gmail.com

Curriculum

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32 lectures ∙ (5hr 41min)

Course Materials:

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