Build an In-house Document AI Chatbot in Just 1 Hour - With RAG and LangChain (feat. Source Code Provided)

[Source Code Provided] No coding knowledge required. Build it instantly in your browser using Google's latest tool (IDX) without any installation! Stop studying coding syntax! This is an ultra-fast, hands-on course where you'll build an RAG chatbot that perfectly understands internal company documents through AI conversation (Vibe Coding) in the Google IDX environment and deploy it live to the web.

(4.8) 10 reviews

42 learners

Level Beginner

Course period Unlimited

Python
Python
AI
AI
LLM
LLM
LangChain
LangChain
RAG
RAG
Python
Python
AI
AI
LLM
LLM
LangChain
LangChain
RAG
RAG

Reviews from Early Learners

4.8

5.0

kyujong.roh

100% enrolled

I was hesitant to use external AI due to security concerns, but by learning how to build my own AI mentor in a local environment, I have established clear practical guidelines.

5.0

daniel.na

100% enrolled

I kept getting messages saying the Gemini API limit was exceeded, so I used ChatGPT instead. I'm happy that I was able to produce clean results within an hour. I'm looking forward to the next lecture.

5.0

tata

71% enrolled

The lectures are short and concise, which is great. The big advantage is that you can deploy your own AI assistant on the web with just an hour or two of investment over the weekend. Even non-majors can easily follow along.

What you will gain after the course

  • Your Own Full-Stack AI Service: Master the entire process of building a RAG-based web service that provides accurate answers by learning from internal confidential documents or personal data.

  • Mastering AI orchestration: You will acquire 'Vibe Coding' capabilities—a next-generation development paradigm where you complete services by giving sophisticated instructions to AI instead of writing complex code yourself.


No more AI hallucinations! Catch them with RAG

I have prepared this course for those who want to create their own AI assistant by mastering RAG technology,
which solves the critical drawback of LLMs: hallucinations.


When you need the latest information every time, but the AI only gives irrelevant answers

When you want to make AI understand internal security documents but feel overwhelmed about how to start

When you want to get accurate and reliable answers from AI, but find the actual implementation difficult

Do you want to quickly create practical results instead of just theory?
Start your own AI era right now with RAG and LangChain.


From AI hallucinations
to the necessity of reflecting the latest information, grasp the core principles of RAG
quickly and easily.

Build an AI chatbot based on actual internal documents, deploy it to the web, and
become your own AI assistant expert.





✔️

Build your own in-house AI assistant now

Building a Custom AI Assistant for Our Company
with RAG and LangChain

We guide you through the entire process of building a RAG-based chatbot that solves the LLM hallucination problem and provides accurate answers by learning from internal company documents or personal materials. Instead of complex coding, you can quickly complete a functional end product through 'Vibe Coding,' where you simply give instructions to the AI.

AI Assistant Website

Practical Chatbot Development in the Google Gravity IDE Environment

In the Google Gravity IDX environment, you will participate in a hands-on session to build an AI chatbot that understands internal documents using RAG and LangChain, and deploy it in real-time as a website. You will gain experience in directly creating a fully functional full-stack AI service.

Gravity IDE

Acquiring AI Orchestration Capabilities Based on Vibe Coding

You will acquire 'Vibe Coding' capabilities, which involve giving sophisticated instructions to AI using the latest AI technologies such as LLM, RAG, and LangChain to achieve desired outcomes. Even those who are tired of learning coding syntax can quickly gain practical experience in building AI services.

Acquiring AI Command Capabilities Based on Vibe Coding


📚

Build your own AI assistant
without AI hallucinations

The necessity of RAG and an introduction to LangChain

Section 1

The Necessity of RAG and Introduction to LangChain

This section explains the working principles and necessity of RAG (Retrieval-Augmented Generation) to address the issue of LLM hallucinations. It also introduces the role and core components of the LangChain framework, which simplifies complex RAG implementations.


Setting up the development environment and building a customized chatbot

Section 2

Setting Up the Development Environment and Building a Custom Chatbot

It covers how to set up an actual development environment, centered on the Google IDX environment. Afterwards, through the process of issuing an LLM API key, a customized RAG chatbot capable of answering questions based on internal documents or personal materials will be built.


AI Assistant Website

Section 3

Web Service Deployment and Improvement of RAG Chatbot

We will deploy the built customized RAG chatbot as a website so that external users can easily access and utilize it. We will enhance the service's quality by applying various measures to improve the user experience (UX).


We can solve the concerns of people like this!


📌

Non-majors and aspiring solo entrepreneurs

Those who are tired of studying theory and want to quickly create a 'real working result' but felt lost on where to start
Those who want to master the entire process of building an RAG chatbot that perfectly understands internal documents through AI conversation and deploying it in real-time to the web

📌

Current planners and office workers

Those who have been considering automating internal documents or introducing a dedicated AI assistant for their team, but lacked knowledge on technical implementation methods
Those who want to acquire 'Vibe Coding' skills, a next-generation development paradigm where you complete results by instructing AI instead of writing complex code yourself

📌

Developers with little experience in AI service development

Those who have had difficulty ensuring the reliability of AI services due to LLM hallucination issues
Those who want to efficiently build complex RAG systems using frameworks such as LangChain




Notes before taking the course


Practice Environment

  • Operating System: Windows, macOS, and Linux are all supported.

  • Development Tools: Vibe Coding environment, Google IDX, or VS Code are recommended.

  • PC Specifications: RAM 8GB or higher is recommended for a smooth development environment.

  • LLM, RAG, Artificial Intelligence (AI)

Prerequisite Knowledge and Important Notes

  • It is helpful to have a basic understanding of coding syntax.

  • An interest in AI technology trends is required.

  • We focus on creating actual results rather than theory.

Learning Materials

  • Lecture slide PDFs are not provided.

  • Since the course is practice-oriented, you will learn by writing the code yourself.

  • Learn how to use relevant open-source libraries (such as LangChain).


Recommended for
these people

Who is this course right for?

  • Non-majors and aspiring solo entrepreneurs who are tired of theoretical study and want to quickly build 'real, working results.'

  • Planners and professionals who are considering internal document automation or implementing a dedicated AI assistant for their team, but feel lost on where to start.

Need to know before starting?

  • The absolute basics of Python: It's enough if you've just heard of what variables and functions are.

  • Google Account: Please prepare only a Google account to use Google IDX and the Gemini API.

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4.8

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Courses

I share knowledge by combining the know-how gained through direct challenges with new trends.

Experience

  • Master's program in AI in Silicon Valley, USA

  • Developer at a major domestic IT corporation (6+ years)

  • Currently developing and operating 14 Android apps, 7 iOS apps, and websites

     

 

[Eng]

Based on my existing experience and expertise, I'm sharing know-how and tips I want to share while following world trends. Thank you for your cooperation!

Experience

Developer at a major IT corporation in South Korea (6y +)

Bachelor's degree in Computer Engineering

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Reviews

All

10 reviews

4.8

10 reviews

  • danielna5496님의 프로필 이미지
    danielna5496

    Reviews 3

    Average Rating 5.0

    5

    100% enrolled

    I kept getting messages saying the Gemini API limit was exceeded, so I used ChatGPT instead. I'm happy that I was able to produce clean results within an hour. I'm looking forward to the next lecture.

    • codebridge
      Instructor

      Thank you for taking the course!! I will be back with more informative and interesting topics in the next lecture.

  • tata님의 프로필 이미지
    tata

    Reviews 10

    Average Rating 5.0

    5

    71% enrolled

    The lectures are short and concise, which is great. The big advantage is that you can deploy your own AI assistant on the web with just an hour or two of investment over the weekend. Even non-majors can easily follow along.

    • codebridge
      Instructor

      Thank you for taking the course. ☺️ I will continue to create many more informative lectures in the future.

  • kyujongroh1518님의 프로필 이미지
    kyujongroh1518

    Reviews 10

    Average Rating 5.0

    5

    100% enrolled

    I was hesitant to use external AI due to security concerns, but by learning how to build my own AI mentor in a local environment, I have established clear practical guidelines.

    • codebridge
      Instructor

      Thank you for taking the course! I'm glad to hear it was helpful. As mentioned during the lecture, if you want to further strengthen security, please keep in mind that there is also a way to run LLMs in a local environment. 😊

  • baekdongmyoung5886님의 프로필 이미지
    baekdongmyoung5886

    Reviews 3

    Average Rating 5.0

    5

    100% enrolled

    • rlatnstn298593님의 프로필 이미지
      rlatnstn298593

      Reviews 1

      Average Rating 5.0

      5

      50% enrolled

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