Unleash the Power of Large Language Models Using LangChain

Discover how to leverage LangChain through our LangChain course for the development of LLM-powered applications. Learn about prompt templates, chains, memory types, and tools to build AI applications.

Beginner

14 Lessons

Certificate of Completion

AI-POWERED

Explanations

AI-POWERED

Explanations

This course includes

20 Playgrounds

This course includes

20 Playgrounds

Course Overview

Unlock the potential of large language models (LLMs) with our beginner-friendly LangChain course for developers. Founded in 2022 by Harrison Chase, LangChain has revolutionized GenAI app development. This interactive LangChain course integrates LLMs into AI applications, enabling developers to create smart AI solutions. Enhance your expertise in LLM application development and LangChain development. Explore LangChain’s core components, including prompt templates, chains, and memory types, essential for ...Show More

What You'll Learn

A comprehensive understanding of LangChain and its capabilities for AI application development

The ability to build robust GenAI apps and automate workflows using LangChain

Hands-on experience implementing a chatbot that responds to queries in multiple languages using the router chain in LangChain

Using retrieval-augmented generation to answer questions and find information retrieval efficiently

The ability to explore LangGraph basics to create dynamic multi-agent systems for adaptable AI workflows

What You'll Learn

A comprehensive understanding of LangChain and its capabilities for AI application development

Course Content

Introduction to LangChain

Get familiar with leveraging LangChain and large language models for GenAI solutions.

What Is a Language Model?

What Is LangChain and Why Does It matter?

Use Cases of LangChain

Exploring LangChain

Work your way through LangChain’s chat models, prompt templates, output parsers, runnables, tools, and vector stores.

Chat Models, Messages, and Prompt Templates in LangChain Parsing Outputs with LangChain Runnables and Expression Language Tools in LangChain Embeddings and Vector Stores in LangChain

LangGraph Basics

Explore LangGraph’s dynamic multi-agent systems for adaptable AI workflows. Understand the main components of LangGraph and how to use them.

What Is LangGraph?What Are the Main Components of LangGraph?Why Traditional Chains Fall Short?How to Create a Routing System Quiz: Introduction to LangGraph

Wrapping Up

Take a closer look at integrating LangChain with LLMs, dynamic agents, and future possibilities.

Conclusion

Query CSV Files with Natural Language Using LangChain and Panel

Project

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

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Explain with AI

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