Enroll Course: https://www.udemy.com/course/nadocoding-langchain/
Are you fascinated by the power of AI and conversational models like ChatGPT? Do you want to move beyond simply interacting with AI and build your own intelligent systems? Then this Udemy course, “챗GPT를 넘어서! 랭체인(LangChain)과 RAG로 만드는 AI 문서 Q & A 챗봇” (Beyond ChatGPT! Creating an AI Document Q&A Chatbot with LangChain and RAG), is exactly what you need.
This project-based course offers a comprehensive introduction to building Retrieval-Augmented Generation (RAG) systems using LangChain. It’s designed for anyone eager to create AI that can provide smart, data-driven answers from your own documents. Forget dry theory; this course focuses on hands-on experience, guiding you through the entire process of building a RAG system from scratch.
**What You’ll Achieve:**
The primary goal of this course is to empower you to build a RAG system from start to finish using LangChain. You won’t just learn the concepts; you’ll actively experience the workflow and understand how it all works. By the end, you’ll be equipped to develop your own AI-powered document Q&A systems, going far beyond basic AI usage.
**Prerequisites:**
Don’t worry if you’re not an AI expert or a seasoned developer! The course is accessible to those with a few foundational skills:
1. **Basic Python:** Familiarity with variables, lists, dictionaries, functions, conditional statements, and loops is sufficient.
2. **ChatGPT Experience:** Having used ChatGPT, understanding how to input prompts, and receiving responses is enough. Knowing the role of prompts and how to communicate with the model is beneficial.
3. **Basic Prompt Engineering Concepts:** A light understanding of prompt engineering is helpful, as the course separates system and user messages.
**Course Structure:**
The course unfolds in a logical, step-by-step manner:
1. **LangChain Fundamentals:** Understanding the basics and usage of LangChain.
2. **Document Loading & Splitting:** Importing and segmenting your data.
3. **Embeddings & Vector Stores:** Transforming data into a searchable format using embedding models.
4. **Information Retrieval & Response Generation:** Searching for relevant information based on user queries and generating responses.
5. **Project Completion:** Integrating all components into a fully functional RAG system.
Each step includes practical code examples and exercises. Complex concepts are explained in a clear and intuitive way.
**Who Should Enroll?**
* Individuals who want to build their own AI services beyond ChatGPT.
* Those interested in document-based Q&A systems and RAG.
* Beginners looking to learn LangChain through practical application.
* Aspiring developers and planners aiming to hone their AI and development skills with real-world projects.
This course promises to demystify RAG systems and provide you with the knowledge and confidence to implement them in your own projects. In just about 6 hours, you’ll gain invaluable skills. Ready to start building?
*Note: An OpenAI API Key is required for this course (estimated cost $5). Instructions for obtaining one are provided within the course.
Enroll Course: https://www.udemy.com/course/nadocoding-langchain/