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AI Agent Development

Learning Python Chatbot & RAG through Projects - Using LangChain, Gradio

Using Python's basic syntax and libraries, create your own AI chatbot. You will carry out 5 projects step-by-step, including PDF document-based RAG, and learn the process of deploying them as web services.

(4.9) 31 reviews

346 learners

  • pdstudio
토이프로젝트
이론 실습 모두
RAG
LangChain
LLM
ChatGPT
Chatbot

Reviews from Early Learners

What you will learn!

  • LangChain Basic Syntax Required for LLM Application Development

  • PDF document-based Simple RAG implementation

  • LangChain Agent and CrewAI Multi-Agent Implementation

  • Gradio chatbot interface implementation and Huggingface Space deployment

Implementing with Python
The first step to creating your own AI chatbot 🤖


If you know Python, creating your own chatbot isn't difficult.
Quickly build a GPT-based chatbot with five easy-to-follow, hands-on projects !


It's a simple and easy project, but it packs a lot into it.

A curriculum that covers all core technologies and concepts related to LLM (Langchain, RAG, Multi Agent)
Quickly implement a variety of work-related chatbots, from Q&A and document reading to data and investment analysis.
Detailed structure that moves from easy projects to the next step step by step

  • A Simple QA Chatbot : Setting Up the Development Environment, LLM Chain Structure, Understanding the Gradio Interface, and Tips for Good Prompts

  • PDF Chatbot : Understanding the RAG Technique, Understanding Model Parameters, and Implementing a Chatbot Interface

  • Data Analysis Chatbot : Upload a CSV file and analyze the data (LangChain Agent)

  • Cryptocurrency Investment Analysis Chatbot : Cryptocurrency Research and Investment Analysis (Sequential Multi-Agent)

  • Jeju Island Travel Planner : Jeju Island Itinerary Recommendations for Foreign Tourists (Hierarchical Multi-Agent)

I recommend this to these people

I learned Python, but where can I use it?

Using Python's basic syntax
Anyone who wants to develop an application

Want to create your own AI chatbot?

Chatbot development and web service deployment
For those who want to experience it firsthand

Want to learn generative AI?

I'm interested in generative AI and LLM.
Those who are at a loss as to how to implement it


With a chatbot project I created myself
One step closer to AI service development!

After taking this course, you too can become an AI chatbot developer. The four projects you create will serve as a meaningful first portfolio. By implementing chatbots yourself, we hope you will develop new ideas and problem-solving skills as you navigate the future service changes brought about by AI.

Get started today and take your first step into the world of AI chatbot development. You'll experience how your chatbots can solve real-world problems , and it'll be the perfect starting point for your journey as an AI service developer .

Lecture Features ⭐️

1⃣ Hands-on project-based learning

This course is structured to guide students through the entire process of developing and deploying an AI chatbot using Python, step-by-step, through five practical projects . Combining theory and practice, students will be able to create a usable chatbot themselves.

Learning materials

2⃣ Understanding and utilizing the latest LLM technology

This course delves into how to develop chatbots using cutting-edge technologies like GPT and the LangChain development tool . You'll learn advanced technologies like RAG and Multi-Agent and how to apply them to real-world chatbot development. It also guides you through creating effective prompts to improve response quality (few-shot, chain-of-thought).

LangChain

3⃣ Implement web apps quickly and easily using Gradio

This course uses the open-source library Gradio to create an AI web application with just a few lines of Python code . It covers all of Gradio's main interfaces (Interface, ChatInterface, and Blocks), enabling students to present their projects more quickly and efficiently.

Gradio

Things to note before taking the course

Practice environment

  • Operating System and Version (OS): Lectures will be conducted based on Windows (Linux and MacOS users can also practice)

  • Tools used: VS Code, OpenAI API authentication key required (separate fee may apply)

  • PC specifications: Not applicable

Learning Materials

Player Knowledge and Precautions

  • Those with basic knowledge of Python (those who can do basic programming)


  • If you have any questions or comments, please feel free to ask.

Linked Lecture Guide (1)

  • RAG Master: From Basics to Advanced Techniques (feat. LangChain)

  • From RAG implementation to performance evaluation -

    Practical AI Development in 9 Hours

    • LangChain-based RAG system construction practice

    • Learn advanced RAG techniques

    • RAG System Performance Evaluation Methodology

    • LangChain's latest LCEL syntax and how to use Runnable


  • Link: https://inf.run/mdYe4

Linked Lecture Guide (2)

  • LLM Data Analytics - From Web Crawling to Recommendation Systems

  • Upgrading to LangChain and LLM

    Web Crawling & Data Analysis


    • Data collection using web crawling/scraping

    • Data collection, cleaning, and analysis using LangChain tools and LLM

    • Predictive analytics using LLM (sentiment analysis, summarization, product recommendations, etc.)

  • Link: https://inf.run/QYw3Q

Linked Lecture Guide (3)

  • RAG system implemented with AI agents (w. LangGraph)

  • An intelligent AI agent for augmented search generation (RAG) implemented with LangGraph.


    • Design and Implementation of an AI Agent Structure Using LangGraph

    • Applying AI agents to Retrieval-Augmented Generation (RAG)

    • Expanding the capabilities of AI agents by implementing tool calling functionality.

    • Mastering the latest agent RAG architectures, including Adaptive RAG, Self RAG, and Corrective RAG.

  • Link: https://inf.run/hTwjC

Recommended for
these people

Who is this course right for?

  • Those who want to develop real applications after learning Python

  • Those interested in LLM but unsure how to begin.

  • Those wishing to experience from program development to web service deployment.

  • People wanting real project & code-based classes.

Need to know before starting?

  • Python

Hello
This is

13,694

Learners

481

Reviews

133

Answers

4.8

Rating

7

Courses

안녕하세요. 저는 파이썬을 활용한 데이터 분석 및 인공지능 서비스 개발 실무를 하고 있습니다. 관심 있는 주제를 찾아서 공부하고 그 내용들을 많은 분들과 공유하기 위해 꾸준하게 책을 집필하고 인공지능 강의를 진행해 오고 있습니다.

 

[이력]

현) 핀테크 스타트업 CEO

전) 데이콘 CDO

전) 인덕대학교 컴퓨터소프트웨어학과 겸임교수

Kaggle Competitin Expert, 빅데이터 분석기사

 

[강의]

NCS 등록강사 (인공지능)

SBA 서울경제진흥원 새싹(SeSAC) 캠퍼스 SW 교육 ‘우수 파트너 선정’ (Python을 활용한 AI 모델 개발)

금융보안원, 한국전자정보통신산업진흥회, 한국디스플레이산업협회, 대구디지털산업진흥원 등 강의

서울대, 부산대, 경희대, 한국외대 등 국내 주요 대학 및 국내 기업체 교육 경험

  

[집필]

 

[유튜브] 판다스 스튜디오 : https://youtube.com/@pandas-data-studio?si=XoLVQzJ9mmdFJQHU

Curriculum

All

32 lectures ∙ (3hr 59min)

Course Materials:

Lecture resources
Published: 
Last updated: 

Reviews

All

31 reviews

4.9

31 reviews

  • 전용석님의 프로필 이미지
    전용석

    Reviews 1

    Average Rating 5.0

    5

    19% enrolled

    강의 내용 뿐만 아니라 짚어주시는 기술 동향이 많이 도움이 되었습니다.

    • 판다스 스튜디오
      Instructor

      감사합니다! 😊

  • hakjuknu님의 프로필 이미지
    hakjuknu

    Reviews 155

    Average Rating 5.0

    5

    9% enrolled

    great!

  • 안녕AI님의 프로필 이미지
    안녕AI

    Reviews 3

    Average Rating 5.0

    5

    100% enrolled

    흥미롭게 강의 잘 들었습니다. 코드 로직, 파라미터, 변수 등의 설명을 정말 꼼꼼하게 해주셔서 좋았어요. 코드를 잘 이해시켜 주신다는 점이 강사님의 큰 매력이신 것 같다고 생각합니다ㅎㅎ. 다음에도 좋은 강의 기대하겠습니다. 감사합니다!

  • stiger님의 프로필 이미지
    stiger

    Reviews 25

    Average Rating 4.8

    5

    100% enrolled

    langchain이 무엇인 지 감이 잡힌 것 같습니다!

  • jwoo.song님의 프로필 이미지
    jwoo.song

    Reviews 6

    Average Rating 5.0

    5

    19% enrolled

    $40.70

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