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AI Agent Development

Work Automation AI Agent Ready for Immediate Use in Companies (w. n8n, LangGraph)

Artificial Intelligence, AI, agents... They might seem grand, but once you try them, they're not as difficult as you think. That's why it's important to implement simple features yourself. Through practical projects that can actually be used at a company, you'll directly experience various use cases and learn how to utilize and apply AI agents.

(4.8) 106 reviews

5,699 learners

Level Basic

Course period Unlimited

  • jasonkang
n8n
n8n
AI
AI
LangChain
LangChain
Generative AI
Generative AI
LangGraph
LangGraph
n8n
n8n
AI
AI
LangChain
LangChain
Generative AI
Generative AI
LangGraph
LangGraph

Reviews from Early Learners

What you will gain after the course

  • Raising an obedient(?) and complaint-free junior

  • Ah... training junior staff for thankless jobs.

  • Learn AI Use Cases Ready for Company Use

오뜨 띠배너 (1)

Curious about how companies that work well these days
use AI?

For those who found AI adoption overwhelming, we've prepared 5 automation cases verified in actual work environments. Meet the smart AI agents in our course that will boost your productivity and protect your work-life balance!

If you're having these concerns, I recommend it!

Our company is also telling us to try using AI... How do I get started with AI?

Isn't there a truly practical AI that helps with real work instead of ChatGPT?

How do other companies use it that makes AI so efficient?

Create your own AI assistant for immediate workplace use
with n8n and LangGraph

6 Use Cases Proven in Large Enterprise Practice

Leading enterprise AI projects and directly validating cases, I've selected only 6 use cases that actually delivered results. These aren't simple examples, but workflows currently being used in real organizations.

Powerfully with the latest tool combination of n8n and LangGraph

You can create flexible AI agents by combining n8n and LangGraph. Repetitive tasks can be easily automated through n8n, while more complex flows or external system integrations add design depth with LangGraph.

True automation is customizing it to fit my work

It's difficult to create automation that fits my work by just following predetermined use cases. This course allows you to break down tasks into smaller parts and implement them progressively, helping you learn the thought process for designing AI automation that suits your specific tasks.

n8n and LangGraph Meet
Smarter AI Agents

The hottest no-code tools for work automation these days

✅ (No-code) Automation design with just drag and drop
✅ (Scalability) Integration with various apps and AI services
✅ (Flexibility) Support for complex flows including conditional branching and loops
✅ (Security) Safe data processing through self-hosting

Essential Tools for Smarter Agents

✅ (Advanced) Automation design possible even when difficult with n8n alone
✅ (Visualization) AI agent flow visible at a glance
✅ (Precision) Flexible control of response methods according to situations
✅ (Scalability) Free integration with various tools and APIs

I recommend this for people like this

3 employees need to do the work of 10 people.Daily competitor news checks, customer inquiry responses, business report writing... If you're doing all of this manually?
For
small team leaders who want to save time with AI automation

I want to solve it myself without help from the development team.
Do you feel awkward asking "Could you please extract this data for me"? For
non-technical roles who want to analyze data in natural language without knowing SQL and automate news monitoring

I just want to focus on development.
Coding is fun, but repetitive task handling, client communication, and project management are bothersome, right? For
solo entrepreneurs who want to automate tedious tasks with AI Agents and focus on core development work

🚀 After taking the course, you'll discover this version of yourself

  • Person suggesting AI automation ideas in team meetings

  • A person who delegates repetitive tasks to AI and focuses on creative work

  • Someone who sees a problem and immediately thinks of automation solutions

6 Use Cases for Building
Practical AI Agents

Help me write an email.

n8nstreamlit
This is an email assistant agent that reads emails on your behalf, determines if a reply is needed, and even writes drafts that fit the context. You can build workflows with n8n and create a beautiful UI for the email bot using Streamlit.

You can automatically receive articles from our company.

[[CODE_1]]n8n[[/CODE_1]][[CODE_2]]spreadsheet[[/CODE_2]][[CODE_3]]notion[[/CODE_3]]

You can collect articles related to our company, run sentiment analysis on them, and then organize them in Google Sheets or Notion, or receive them directly via email. All of this can be easily created with n8n.

Save time searching internal documents.

n8nLangGraph
Ask what's in your company documents and AI will find it for you! You can create an internal Q&A chatbot using n8n. Also, let's build an agent using LangGraph for more sophisticated responses.

Data analysis is possible even without knowing SQL.

n8nsupabase
Create an agent that automatically generates SQL queries when you ask questions in everyday language and receive answers via Slack. No more requesting data from the development team.

AI Code Reviewer That Saves Developers' Time

LangGraphn8nMCP

Code quality checks, security issue reviews, and improvement suggestions all automated! Experience how your development team's productivity doubles!

Agent that summarizes YouTube and videos

[[CODE_1]]LangGraph[[/CODE_1]][[CODE_2]]MCP[[/CODE_2]]

Do you want to share recorded internal training materials or great videos you've found on YouTube with your team members? While external solutions exist, are you concerned about internal materials being leaked? With LangGraph, you can implement this simply with less than 100 lines of Python code. We'll also show you how to modularize the nodes used in LangGraph so you can easily reuse them when similar functionality is needed.

Pre-enrollment Reference Information

Practice Environment

  • n8n runs using Docker, so you can follow along regardless of your operating system

  • You can also follow along with LangGraph if you have Python installed.


Learning Materials

  • I provide Notion links and GitHub source code

  • The workflow created with n8n is included in the course materials.

Prerequisites and Important Notes

  • n8n requires no prior knowledge

    • Since it's GUI-based and you can create workflows through drag and drop, it shouldn't be too difficult even without development knowledge.

  • LangGraph requires Python experience.

Recommended for
these people

Who is this course right for?

  • Person getting pressed by boss for AI adoption.

  • People wanting to know how other companies use AI

  • "Is this really that amazing?" For those who are curious

  • For those who want to apply AI in their work but don't know where to start.

Need to know before starting?

  • Python(Req.)

  • LangChain(optional)

Hello
This is

15,203

Learners

1,052

Reviews

457

Answers

4.9

Rating

9

Courses

Curriculum

All

31 lectures ∙ (5hr 56min)

Course Materials:

Lecture resources
Published: 
Last updated: 

Reviews

All

106 reviews

4.8

106 reviews

  • jinsyu8118님의 프로필 이미지
    jinsyu8118

    Reviews 1

    Average Rating 5.0

    5

    89% enrolled

    I urgently needed to create a POC for a RAG project that came up suddenly, and while looking for suitable lectures, I tried a preview lecture and immediately purchased the roadmap. I quickly went through it once without hands-on practice, just to skim through the concepts. Since I started using cloud code, I felt like I could build anything on my own. Now I truly feel like I can build anything. The project contract cost (with the project contract being certain if I just create a good POC) is hundreds of times more than the instructor's roadmap cost - I don't know where else you can find such cost-effectiveness. Here are the lecture advantages I experienced: 1. Clear pronunciation and good delivery. 2. It's realistic because it contains processes with mistakes/typos rather than being a perfect lecture without any errors. 3. References documents including papers are mentioned. 4. Introduces various tips that can only be known through actual work experience (line breaks in pdf parsing/prompt writing/table and image processing...). 5. English pronunciation isn't strange? (Many instructors pronounce basic English words ridiculously, which was often bothersome, but there were no such cases here) 6. Important concepts are repeated dozens of times. You'll understand eventually. When I first listened to the LangGraph lecture and heard mentions of edge/node/state, I wondered what it was about. But just watching the same process being created hundreds of times, I think I roughly understand it now. I usually don't leave course reviews, but I strongly recommend this for those learning langchain/langgraph/rag.

    • jasonkang
      Instructor

      Thank you for the great feedback! Your course review seems to explain the lecture's intent better than I could. I intentionally left error-prone sections unedited, which might have been inconvenient, but thank you for seeing them positively. It seems the intention was well conveyed. I hope you create a great POC and achieve good results. I'll continue to support you!

  • sumin220님의 프로필 이미지
    sumin220

    Reviews 5

    Average Rating 5.0

    5

    30% enrolled

    The process of directly seeing how the shallow knowledge of artificial intelligence I learned during my undergraduate years could be applied in practical work was extremely interesting. In particular, I was able to gain many ideas through the lectures and tried to apply them immediately. Recently, at a hackathon, there was a task where I needed to generate different random topics for 40 teams. What would have taken a long time if done manually was completed in just 20 minutes thanks to the AI agent. That moment was truly thrilling. Also, I really appreciated how Byungjin showed the process of solving problems when errors occurred during the lectures. Rather than simply providing the correct answers, I was able to gain great insights by watching the process of analyzing problems and finding solutions. I feel like I'm experiencing firsthand the tremendous benefits that come from automation!

    • jasonkang
      Instructor

      If you came up with ideas to apply agents right away after just taking the first part of the course, it seems like you're already putting a lot of thought into work efficiency and automation on a regular basis. As I mentioned in the course introduction, even though it might seem a bit difficult at first, once you try it, you'll feel like 'Oh, it's nothing special.' So I think AI will gradually become more naturally integrated into Sumin's daily work going forward. I'll continue to support you in creating more automation with Sumin's ideas and speed! 🚀

  • brbr님의 프로필 이미지
    brbr

    Reviews 3

    Average Rating 5.0

    5

    33% enrolled

    The fast-paced progression (though I am watching at 1.2x speed) and this feeling like a mentor at work is sharing only the essential gems! It's exciting and great! 😆

    • y2kkorean님의 프로필 이미지
      y2kkorean

      Reviews 6

      Average Rating 5.0

      5

      33% enrolled

      • gksruf99399362님의 프로필 이미지
        gksruf99399362

        Reviews 3

        Average Rating 5.0

        5

        61% enrolled

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