Fundamentals of Retrieval-Augmented Generation with LangChain

Explore this beginner RAG course to learn the basics of retrieval-augmented generation. For hands-on practice, build RAG pipelines using LangChain and create user-friendly applications with Streamlit.

Beginner

21 Lessons

Certificate of Completion

AI-POWERED

Explanations

AI-POWERED

Explanations

This course includes

27 Playgrounds

This course includes

27 Playgrounds

Course Overview

Retrieval-augmented generation (RAG) is a powerful paradigm that combines the strengths of information retrieval and generative AI models to produce accurate, context-relevant results. This method improves the efficiency of generative models by integrating external knowledge sources for various applications. This beginner RAG course introduces learners to the fundamental concepts of RAG, offering a comprehensive understanding of its architecture and applications. You’ll learn how to implement RAG pipelines...Show More

TAKEAWAY SKILLS

Generative Ai

Large Language Models (llms)

What You'll Learn

A clear understanding of the basics of retrieval-augmented generation (RAG)

Practical experience implementing RAG pipelines using LangChain

The ability to build a frontend application for your RAG pipeline using Streamlit

Real-world application of RAG concepts to solve practical problems

What You'll Learn

A clear understanding of the basics of retrieval-augmented generation (RAG)

Course Content

Getting Started

Understand the retrieval-augmented generation (RAG) principles, its architecture, and how it enhances AI accuracy for practical applications.

Why Choose RAG and This Course?

The Basics of RAG

Learn the logic behind RAG, its essential components, and strategies like indexing and retrieval to build a solid foundation for your RAG systems.

Understanding Retrieval and Generative Models What Is Retrieval-Augmented Generation (RAG)?Indexing Essentials: How RAG Organizes Data?Effective Retrieval Strategies for RAG Pipelines Quiz: Test Your Knowledge on RAG Basics

RAGs and LangChain

Explore implementing indexing, querying, and response generation in LangChain to power your RAG systems.

Indexing and Retrieving Documents with LangChain Creating Augmented Queries Using LangChain Generating Context-Driven Responses with LangChain Quiz: Reinforce Your LangChain and RAG Skills

Build a Frontend for Our RAG System

Use Streamlit and LangChain to build a user-friendly frontend for your RAG system, enabling seamless interaction with your pipeline.

What Is Streamlit?—An Intro for Beginners Building a QA System Interface in Streamlit Adding LangChain Logic to Your Streamlit Application Quiz: Test Your Frontend and Streamlit Knowledge

Challenges

Tackle advanced challenges to enhance your system, like handling vector store transitions and supporting multiple file formats.

Challenge: Transitioning Between Vector Stores Solution: Transitioning Between Vector Stores Challenge: Supporting PDF File Uploads in RAG Solution: Supporting PDF File Uploads in RAG Challenge: Building a QA System for Multiple Files Solution: Building a QA System for Multiple Files

Build an Interactive PDF Reader using LangChain and Streamlit

Project

Conclusion

1 Lesson

Tackle practical implementations of RAG systems with LangChain and explore advanced features.

Trusted by 1.4 million developers working at companies

Anthony Walker

@_webarchitect_

Emma Bostian 🐞

@EmmaBostian

Evan Dunbar

ML Engineer

Carlos Matias La Borde

Software Developer

Souvik Kundu

Front-end Developer

Vinay Krishnaiah

Software Developer

Eric Downs

Musician/Entrepeneur

Kenan Eyvazov

DevOps Engineer

Anthony Walker

@_webarchitect_

Emma Bostian 🐞

@EmmaBostian

Hands-on Learning Powered by AI

See how Educative uses AI to make your learning more immersive than ever before.

Instant Code Feedback

Evaluate and debug your code with the click of a button. Get real-time feedback on test cases, including time and space complexity of your solutions.

AI-Powered Mock Interviews

Put your skills to the test in a simulated interview setting. Receive personalized feedback based on your performance. Available in Premium & Premium Plus plans.

Adaptive Learning

At various checkpoints throughout Educative courses, you will be prompted to take a quick assessment. Receive a condensed curriculum tailored to your strengths and skill gaps.

Explain with AI

Select any text within any Educative course, and get an instant explanation — without ever leaving your browser.

AI Code Mentor

AI Code Mentor helps you quickly identify errors in your code, learn from your mistakes, and nudge you in the right direction — just like a 1:1 tutor!