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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.

4.7

20 Lessons

Updated 1 week ago

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LEARNING OBJECTIVES

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

Learning Roadmap

20 Lessons3 Quizzes

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

Build an Interactive PDF Reader using LangChain and Streamlit

Project

Premium

LangGraph Basics

5 Lessons

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

Advanced LangGraph

6 Lessons

Master the integration of multiple tools in LangGraph for dynamic AI workflows.

Wrapping Up

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

Conclusion

Certificate of Completion

Showcase your accomplishment by sharing your certificate of completion.

Developed by MAANG Engineers

Every Educative lesson is designed by a team of ex-MAANG software engineers and PhD computer science educators, and developed in consultation with developers and data scientists working at Meta, Google, and more. Our mission is to get you hands-on with the necessary skills to stay ahead in a constantly changing industry. No video, no fluff. Just interactive, project-based learning with personalized feedback that adapts to your goals and experience.

ABOUT THIS COURSE

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 automating workflows and managing conversational contexts. Learn how to connect language models with tools and data via APIs, utilizing agents to expand your applications. You’ll also try out RAG and see how it helps answer questions. Additionally, the course covers LangGraph basics, a framework for building dynamic multi-agent systems. Understand LangGraph’s components and how to create robust routing systems.

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