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From LLM Fundamentals to the Latest RAG & LangChain: Master the LLM Basics Course in Just 5 Hours!

This is a course to master the fundamental theories of LLM and the core technologies of LangChain and RAG. You can easily learn the latest AI technologies used in practice, starting from LLM basics!

(4.4) 27 reviews

154 learners

Level Basic

Course period Unlimited

Chatbot
Chatbot
LLM
LLM
LangChain
LangChain
RAG
RAG
openAI API
openAI API
Chatbot
Chatbot
LLM
LLM
LangChain
LangChain
RAG
RAG
openAI API
openAI API

Reviews from Early Learners

Reviews from Early Learners

4.4

5.0

이종찬

31% enrolled

I recommend this course because it explains things in an easy-to-understand way

5.0

김은종

100% enrolled

😊

5.0

welovearum

100% enrolled

I can now understand and utilize LLMs more deeply!

What you will gain after the course

  • Basic Concepts and Practical Applications of Modern LLMs

  • OpenAI API Utilization and Practice

  • Automation and AI Chatbot Development Using LangChain

  • Hands-on RAG-based Application Development

LLM Hackers: Perfect Mastery of the Latest AI Technology with LangChain and RAG🤔

Do RAG and LangChain still feel difficult to you? 🤔

Here's a course where LLM beginners can learn the latest AI technology with easy explanations and acquire skills to apply in real-world practice.

This course teaches you LLM, RAG, and LangChain in an easy and systematic way, even though they may seem complex.

Make the latest AI technology your own quickly and effectively with LLM Hackers, perfectly structured from theory to practice.



[LLM Fundamentals and Latest Technologies including RAG, Langchain] 🎥


[RAG code used in actual practice provided]








💡What will you learn from this course?

  • From LLM Basics to Practical Application


    You'll learn the fundamental principles of language models and the latest technological developments, and how to apply them directly to practical work.

  • Build Real-World Projects with OpenAI API
    Create high-quality projects such as review analysis and automated blog generation using ChatGPT API and Function Calling


  • LangChain Concepts and Practical Projects
    Experience various hands-on projects including review response generation, data analysis, and MYSQL DB analysis using the powerful LangChain.

  • Solve complex data problems with RAG
    Learn vector store design, PDF Q&A, and search systems using web data.


Key Features of This Course

📌Comprehensive Coverage of the Latest LLM Technologies

  • You can learn the hottest AI technologies right now, including LLM, LangChain, and RAG, all at once.
    Apply them directly to your projects with detailed code provided..

  • This is a course where you can master the overall technology of LLM in a short period of time.

📌 Hands-on Practice Curriculum

20% theory, 80% hands-on practice
Go beyond simple concept understanding by writing directly executable code and verifying results.

📌 High-Quality Real-World Projects

  • Review Sentiment Analysis Automation

  • PDF-based Q&A Application

  • SQL Data Analysis with LangChain

📌 Easy explanations for beginners
A curriculum structured step-by-step from the basics so that even beginners can easily get started.

We recommend this for

I want to learn LLM and RAG

"I don't know where to start..."

→ We'll guide you on the easiest and fastest path to learning.


Those who want to apply AI technology in practical work
Those who want to analyze data and carry out projects using LLM and LangChain

Those who want to develop customized LLMs with RAG
We explain RAG used in business in an easy-to-understand and concise way.

💡 After taking this course, you will experience these changes 🌟

  • You can overcome the limitations of LLMs with LangChain and RAG.

  • Learn the fundamentals of agents with OpenAI API and Function Calling features. với OpenAI API và tính năng Function Calling.


  • You can learn the technologies used in LLM-based applications by utilizing the latest techniques.


  • You will design RAG search systems and develop the skills to solve business problems.


  • Non-majors and beginners can learn practical AI technologies and upgrade their career to the next level.

Here's what you'll learn.

LLM Theory and Prompt Engineering

  • Understand the basic principles and development process of LLMs, and learn effective prompt design methods.


Practical LangChain Applications

  • Learn practical projects from explanations of LangChain modules to building RAG-based PDF search systems that handle various data types, and SQL DB analysis.


From basics to advanced RAG, the latest LLM technology

  • You will learn vector store design, PDF-based question-answering system construction, web data-based question-answering system construction, and more.

  • Text summarization techniques for processing large volumes of text, LangChain Hub integration

    You will learn various RAG techniques and more.

OpenAI API Application Projects

Review sentiment analysis, Naver news and blog content generation, and developing web search applications using Function Calling.

Who created this course 👨‍🏫

  • PhD Candidate at AI Graduate School (Specializing in Generative AI and LLM)

  • Operating a company specializing in generative AI and big data analysis


  • Completed over 200 AI/Big Data projects

  • Former Natural Language Processing and Big Data Analysis Researcher at Government-funded Research Institute



Notes Before Taking the Course

Practice Environment

  • Operating System: You can learn without any issues even in a Windows environment.


  • Tools Used: Hands-on practice will be conducted based on the GoogleColab environment.


Learning Materials

  • Theory materials and practice code are provided via Google Sheets.

Prerequisites and Notes

  • You can take this course more effectively if you know Python syntax.

Recommended for
these people

Who is this course right for?

  • Beginner developers and novices who want to start learning LLM

  • AI researchers who want to apply cutting-edge AI technologies like RAG and LangChain in practical work

  • Developers who want to build their own AI solutions

  • A development team aiming to build a customized RAG system for enterprises

Need to know before starting?

  • Basic Python programming knowledge

Hello
This is HappyAI

4,609

Learners

237

Reviews

51

Answers

4.6

Rating

11

Courses

Lee JinKyu | Lee JinKyu

AI·LLM·Big Data Analysis Expert / CEO of Happy AI

👉You can check the detailed profile at the link below.
https://bit.ly/jinkyu-profile

Hello.
I am Lee JinKyu (Ph.D. in Engineering, Artificial Intelligence), CEO of Happy AI, who has consistently handled AI and big data analysis in R&D, education, and project sites.

I have analyzed various types of unstructured data, such as
surveys, documents, reviews, media, policies, and academic data,
based on Natural Language Processing (NLP) and text mining.
Recently, I have been delivering practical AI application methods tailored to organizations and work environments
using Generative AI and Large Language Models (LLM).

We have collaborated with numerous public institutions, corporations, and educational organizations such as Samsung Electronics, Seoul National University, the Office of Education, Gyeonggi Research Institute, the Korea Forest Service,
the Korea National Park Service, and the Seoul Metropolitan Government,
and have conducted more than 200 research and analysis projects across various domains including healthcare, commerce, ecology, law, economics, and culture.

 


🎒 Inquiries for Lectures and Outsourcing

Kmong Prime Expert (Top 2%)


📘 Bio (Summary)

  • 2024.07 ~ Present
    CEO of Happy AI, a company specializing in Generative AI and Big Data analysis

  • Ph.D. in Engineering (Artificial Intelligence)
    Dongguk University Graduate School of AI

     

    Detailed Major: Large Language Models (LLM)

     

    (2022.03 ~ 2026.02)

     

  • 2023 ~ 2025
    Public News AI Columnist
    (Generative AI Bias, RAG, LLM Application Issues)

  • 2021 ~ 2023
    AI & Big Data specialized company Stellavision Developer

  • 2018 ~ 2021
    Government-funded Research Institute Natural Language Processing & Big Data Analysis Researcher


🔹 Areas of Expertise (Lecture & Project Focused)

  • Generative AI and LLM Utilization

    • Private LLM, RAG, Agent

    • Basics of LoRA and QLoRA Fine-tuning

  • AI-based Big Data Analysis

    • Survey, review, media, policy, and academic data

  • Natural Language Processing (NLP) · Text Mining

    • Topic analysis, sentiment analysis, keyword network

  • Public and Corporate AI Task Automation

    • Document summarization, classification, and analysis

       


🎒 Courses & Activities (Selected)

2025

  • LLM/sLLM Application Development
    (Fine-tuning, RAG, Agent-based) – KT

2024

  • LangChain·RAG-based LLM Programming – Samsung SDS

  • LLM Theory and RAG Chatbot Development Practice – Seoul Digital Foundation

  • Introduction to ChatGPT-based Big Data Analysis – LetUin Edu

  • AI Fundamentals & Prompt Engineering Techniques – Korea Vocational Development Institute

  • LDA & Sentiment Analysis with ChatGPT – Inflearn

  • Python-based Text Analysis – Seoul National University of Science and Technology

  • Building LLM Chatbots Using LangChain – Inflearn

2023

  • Python Basics using ChatGPT – Kyonggi University

  • Big Data Expert Course Special Lecture – Dankook University

  • Fundamentals of Big Data Analysis – LetUin Edu


💻 Projects (Summary)

  • Building a Private LLM-based RAG Chatbot (Korea Electric Power Corporation)

  • LLM-based Forest Restoration Big Data Analysis (National Institute of Forest Science)

  • Internal Network Private LLM Text Mining Solution (Government Agency)

  • LLM Model Development based on Instruction Tuning and RLHF

  • Healthcare, Law, Policy, and Education Data Analysis

  • AI Analysis of Survey, Review, and Media Data

Performed over 200 cases, including public institutions, corporations, and research institutes


📖 Publication (Selected)

  • Improving Commonsense Bias Classification by Mitigating the Influence of Demographic Terms (2024)

  • Improving Generation of Sentiment Commonsense by Bias Mitigation
    – International Conference on Big Data and Smart Computing (2023)

  • Analysis of Perceptions of LLM Technology Based on News Article Big Data (2024)

  • Numerous NLP-based text mining studies
    (Forestry, Environment, Society, and Healthcare sectors)


🔹 Others

  • Python-based data analysis and visualization

  • Data analysis using LLM

  • Improving work productivity using ChatGPT, LangChain, and Agents

More

Curriculum

All

48 lectures ∙ (4hr 50min)

Course Materials:

Lecture resources
Published: 
Last updated: 

Reviews

All

27 reviews

4.4

27 reviews

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