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Unleash the Power of Large Language Models Using LangChain

Explore how to leverage LangChain for LLM-powered applications. Gain insights into using prompt templates, chains, memory types, APIs, and retrieval-augmented generation techniques for dynamic app development.

Beginner

15 Lessons

Certificate of Completion

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Explanations

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Explanations

This course includes

19 Playgrounds

6 Quizzes

Course Overview

What You'll Learn

Course Content

Recommendations

Course Overview

LangChain is an open-source framework that facilitates the integration of large language models (LLMs) to develop LLM-powered applications. You’ll start with an introduction to LLMs and the LangChain framework. Next, you’ll learn how to utilize prompt templates to perform repetitive tasks and parse the output of an LLM. You’ll also learn about different types of chains with their use cases. Additionally, you’ll cover different memory types in LangChain to store the chat history. You’ll also learn how to c...Show More

LangChain is an open-source framework that facilitates the integration of large language models (LLMs) to develop LLM-powered ap...Show More

What You'll Learn

An understanding of large language models and why they are preferred in natural language processing tasks

An understanding of the LangChain framework and how it improves over the functionalities of OpenAI

Familiarity with the core components of LangChain, including models, prompt templates, output parsers, chains, and memory

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

The ability to add tools in agents that connect to external information sources through APIs and use the reasoning and action (ReAct) technique

Working knowledge of the retrieval-augmented generation (RAG) technique to implement question answering from a document

An understanding of large language models and why they are preferred in natural language processing tasks

Course Content

Large Language Models

2 Lessons

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

Introduction to the Course

Introduction to Large Language Models

Introduction to LangChain

2 Lessons

Look at how LangChain enhances LLM capabilities, integrating data sources for diverse NLP tasks.

What Is LangChain?

Use Cases of LangChain

LangChain Basics

6 Lessons

Work your way through LangChain's models, prompts, output parsers, chains, router chain, memory, and language routing.

Challenge: Language Routing Using Chains

Advanced Features of LangChain

4 Lessons

Grasp the fundamentals of LangChain's agents, RAG architecture, and question-answering bots.

Agents and Tools

Retrieval-Augmented Generation (RAG)

Hands-On: Question Answering with RAG

Challenge: Agents for Question Answering with RAG

Wrapping Up

1 Lessons

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

Conclusion

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