HomeCoursesUnleash the Power of Large Language Models Using LangChain

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Unleash the Power of Large Language Models Using LangChain
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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.
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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 aut...Show More
Unlock the potential of large language models (LLMs) with our beginner-friendly LangChain course for developers. Founded in 2022...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
The ability to utilize retrieval-augmented generation for efficient question-answering and information retrieval
The ability to explore LangGraph basics to create dynamic multi-agent systems for adaptable AI workflows
A comprehensive understanding of LangChain and its capabilities for AI application development

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Content

1.

Introduction to LangChain

3 Lessons

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

2.

Exploring LangChain

5 Lessons

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

3.

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.

4.

Wrapping Up

1 Lessons

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