강의

멘토링

로드맵

AI Development

/

AI Agent Development

Large Language Models (LLM) for Everyone Part 2 - Building Your Own ChatGPT with LangChain

This is a course to learn the concepts and usage methods of the LangChain library, and to build your own ChatGPT using the LangChain library.

(4.4) 24 reviews

595 learners

  • AISchool
chatgpt
llm
LLM
LangChain
ChatGPT

Reviews from Early Learners

What you will learn!

  • LangChain Library Basics and Usage

  • Retrieval-Augmented Generation (RAG) Concept

  • Various Use Cases of Retrieval-Augmented Generation (RAG) Implementation

  • How to Build My Own ChatGPT with Retrieval-Augmented Generation (RAG)

LangChain for easy LLM implementation,
From concept to practice, all in one place!

Let's implement your own ChatGPT with just a few lines of code using LangChain!

By properly utilizing the LangChain library and the OpenAI API, you can implement your own ChatGPT using the latest LLM model in just a few lines of code.

  • ✅ You can learn step-by-step, from the basic concepts of the LangChain library to various use cases of Retrieval-Augmented Generation (RAG) implementation.
  • ✅ Create your own ChatGPT using the LangChain library!

Who is this course for?

Those who want to learn the concepts and usage of the LangChain library in a solid manner.

Anyone who wants to create their own ChatGPT using Langchain

Anyone who wants to learn about the various use cases of Retrieval-Augmented Generation (RAG)

Anyone who wants to develop a service using the latest LLM model


Lecture Content 📖

👨‍💻 We will practice creating various ChatGPTs of our own using LangChain and various datasets.

We will create JudgeGPT, which allows you to search for case law and check the content of case law using various legal case law data.
Let's create PatentGPT, which allows you to search for patents and check patent information using various patent data.
We will create a review sentiment analysis GPT (SentimentGPT) that can analyze positive and negative sentiments in reviews using various review data.
We will create a Product Recommendation GPT (RecommendationGPT) that recommends products with good ratings and that meet the user's needs using various product review data.

Player Course ✅

👋 This course requires prior knowledge of Python, Natural Language Processing (NLP), and LLM . Be sure to take the courses below first, or have equivalent knowledge before taking this course.


Q&A 💬

Q. What is LangChain?

The LangChain library is a Python library that provides various functions related to natural language processing (NLP) . Its primary purpose is to provide useful tools for building and researching conversational AI systems . Its features include:

1. Chatbot Building : LangChain provides tools for building chatbots and conversational AI systems. This allows users to easily create their own chatbots .

2. Various NLP functions : This library includes various natural language processing functions such as text generation, summarization, and translation.

3. Plug-and-play architecture : Users can easily integrate LangChain with existing NLP models or systems. This allows for the easy combination of various language models and functions.

4. Scalability and Customization : LangChain is designed to allow users to customize and extend the system to suit their needs. This is a valuable feature for researchers and developers.

5. Research and Development Support : LangChain helps researchers and developers experiment with and develop new conversational AI models.

This library is a valuable tool for developers, researchers, and students interested in research and development related to conversational AI . LangChain allows users to more easily build and experiment with complex NLP systems .

Q. Is player knowledge required?

This lecture [Large Language Model for Everyone LLM (Large Language Model) Part 2 - Building Your Own ChatGPT with LangChain] covers how to build your own ChatGPT using the LangChain library and LLM . Therefore, the lecture proceeds under the assumption that you have basic knowledge of Python, natural language processing, and LLM. If you lack basic knowledge of natural language processing and LLM, we recommend taking the preceding lecture [Large Language Model for Everyone LLM (Large Language Model) Part 1 - Fine-Tuning Llama 2] first.

Recommended for
these people

Who is this course right for?

  • Learners of LangChain library concepts and usage.

  • Those who want to build their own ChatGPT

  • Deep learning research job seekers

  • Individuals interested in AI/Deep Learning research

  • Those preparing for AI graduate school

Need to know before starting?

  • Python experience

  • Pre-course: [LLM for Everyone (Large Language Model) Part 1 - Llama 2 Fine-Tuning] Experience

Hello
This is

9,053

Learners

662

Reviews

350

Answers

4.6

Rating

29

Courses

Curriculum

All

46 lectures ∙ (8hr 59min)

Course Materials:

Lecture resources
Published: 
Last updated: 

Reviews

All

24 reviews

4.4

24 reviews

  • dev1님의 프로필 이미지
    dev1

    Reviews 1

    Average Rating 5.0

    5

    100% enrolled

    혼자 학습하기 어려운 부분들을 잘 정리해서 코드로 실제로 진행해볼 수 있게 잘 만들어진 강좌입니다

    • 런던베이글님의 프로필 이미지
      런던베이글

      Reviews 7

      Average Rating 5.0

      5

      100% enrolled

      실습 위주의 강의여서 너무 좋습니다. langchain-community 라이브러리 설치가 곳곳에 빠져있거나 Openai api가 변경된 내용들이 실습 파일에 수정되어있지 않습니다. 저 같은 비전공자 초보자분들은 헤멜수 있고 docstring 찾아보면서 수정해야 됩니다. 미리 변경되면 좋겠으나 조금만 찾아서 수정하시면서 하시면 됩니다. 감사합니다.

      • 이현주님의 프로필 이미지
        이현주

        Reviews 3

        Average Rating 5.0

        5

        61% enrolled

        • 김락근님의 프로필 이미지
          김락근

          Reviews 1

          Average Rating 5.0

          5

          100% enrolled

          • sunbin.lee님의 프로필 이미지
            sunbin.lee

            Reviews 1

            Average Rating 4.0

            4

            100% enrolled

            Limited time deal

            $49,500.00

            25%

            $51.70

            AISchool's other courses

            Check out other courses by the instructor!

            Similar courses

            Explore other courses in the same field!