Udemy ChatGPT and LangChain: The Complete Developer's Masterclass

What you'll learn​

• Integrate ChatGPT into production-style apps with LangChain
• Use LangChain components to build complex text generation pipelines
• Enhance ChatGPT's output by automatically integrating user feedback
• Teach ChatGPT new facts through Retrieval Augmented Generation
• Extend LangChain to implement server-to-browser text streaming
• Use OpenAI Plugins to add new capabilities to ChatGPT, such as database access and code execution
• Understand every line of code we write so you can use these exact same techniques on your own projects
• Build your own chat-with-a-PDF web application, complete with document upload and authentication
• See how users interact with your chat features using observability and tracing

Requirements​

• Basic programming experience with Python

Description​

You've found the most advanced, most complete, and most intensive masterclass online for learning how to integrate LangChain and ChatGPT into production-ready applications!
Thousands of engineers have learned how to build amazing applications using ChatGPT, and you can too. This course uses a time-tested, battle-proven method to make sure you understand exactly how ChatGPT works, and is the perfect pathway to help you get a new job as a software engineer working on AI-enabled apps.
The difference between this course and all the others: you will go far beyond the basics of simple ChatGPT prompts, and understand how companies are integrating text generation into their apps today.
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ChatGPT is being used across industries to enhance applications with text generation. But with this new feature comes many challenges:

1. Building complex text generation pipelines that incorporate outside information
2. Creating reusable configuration components that can be reassembled in different ways
3. Applying user feedback (like upvotes/downvotes) to enhance ChatGPT's output
4. Wiring in observability and tracing to see how users are interacting with your AI
5. Generate text performantly using distributed processing
   This course will walk you through production-ready, repeatable techniques for addressing each of these challenges and many more.
   
   What will you build?

This course focuses on creating a series of different projects of increasing complexity. You'll start from the very basics, understanding how to access ChatGPT 4 programatically. From there, we will quickly increase in complexity, building more complex projects with many more features. By the end, you will make a fully-featured web app that implements a "Chat-with-a-PDF" feature. Note: no previous web development experience is required.
Here's a partiallist of some of the topics you'll cover:

• Understand how complex text-generation pipelines work
• Write reusable code using chains provided by LangChain
• Connect chains together in different ways to dramatically change your apps behavior with ease
• Store, retrieve, and summarize chat messages using conversational memory
• Implement semantic search for Retrieval-Augmented Generation using embeddings
• Generate and store embeddings in vector databases like ChromaDB and Pinecone
• Use retrievers to refine, reduce, and rank context documents, teaching ChatGPT new information
• Create agents to automatically accomplish tasks for you using goals you define
• Write tools and plugins to allow ChatGPT to access the outside world
• Maintain a consistent focus on performance through distributed processing using Celery and Redis
• Extend LangChain to implement server-to-browser text streaming
• Improve ChatGPT's output quality through user-generated feedback mechanisms
• Get visibility into how users interact with your text generation features by using tracing

There are a ton of courses that show how to use ChatGPT at a very basic level. This is one of the very few courses online that goes far beyond the basics to teach you advanced techniques that top companies are using today. I have a passion for teaching topics the right way - the way that you'll actually use technology in the real world.

Who this course is for:​

• Software engineers looking to add AI into their apps