Gen AI - RAG Application Development using LangChain: Mastering LangChain Framework: The Key to Advanced Language Model Applications

Manas Dasgupta

€8.99 ~~€82.99~~

5 (1 Ratings)

Video Jul 2024 8hrs 36mins 1st Edition

Manas Dasgupta

€8.99 ~~€82.99~~

5 (1 Ratings)

Video Jul 2024 8hrs 36mins 1st Edition

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Key benefits

Comprehensive introduction to LangChain and Large Language Models
In-depth exploration of prompts, agents, and tools
Advanced topics including language embeddings and vector databases

Description

This course begins with an introduction to the core concepts of Large Language Models and the LangChain framework. You'll start with the basics of forming prompts and setting up your environment, followed by a code demonstration to solidify your understanding. The first section wraps up with a quiz to test your newfound knowledge. Moving forward, we delve into the fundamental concepts of LangChain. You'll learn about prompt templates, chat prompt templates, and the intricacies of working with agents and tools. As you progress, the course covers advanced topics such as document loaders, output parsers, language embeddings, and vector databases. Practical applications, like creating your first RAG (Retrieval-Augmented Generation) application, are integrated to enhance your learning experience. The final section focuses on real-world RAG applications and projects. You'll work on diverse projects, including SQL data integration, conversational memory, CV search applications, and website query chatbots. By the end of the course, you'll be proficient in analyzing structured data using natural language and creating sophisticated AI-driven applications, ready to apply these skills in real-world scenarios.

Who is this book for?

This course is designed for technical professionals and developers with a basic understanding of Python and AI concepts. Familiarity with natural language processing is a plus but not required. It's perfect for those looking to deepen their knowledge of Large Language Models and the LangChain framework.