English | Size: 329 MB
Genre: eLearning
Introduction to OpenAI API, RAG, LangChain and Vector Stores
What you’ll learn
Learn about ChatGPT and the OpenAI APIs
Build a simple ChatGPT app using Python and OpenAI APIs
Learn about RAG – Retrieval Augmented Generation
Build a RAG based app with ChatGPT
Building safeguards, monitoring performance, ensuring privacy
Other popular use cases for LLM based apps
In the last few years, the tech industry has been upended with the advent of ChatGPT and other Large Language Models.
As you probably know already, ChatGPT is a large language model that uses natural language processing to generate human-like text in response to user prompts. It is now possible for machines to have natural sounding conversations with human beings. In fact, machines can now perform tasks like reasoning, sentiment analysis, translation, code generation and so on. This has opened up many exciting possibilities for enterprise business applications. In this course you will learn the basics of how to work with ChatGPT and build exciting business apps with it.
The course will introduce you to ChatGPT, the basics of OpenAI API and how to invoke the APIs using Python. It will then go on to show you how to build apps using RAG architecture. You will get an introduction to the ChatGPT API, the RAG architecture and the LangChain library.
This is a beginner level course in ChatGPT. It will benefit users who want to get a quick understanding of how to interact with ChatGPT and Python.
If you are a programmer, this will get you started on how to build real world business applications with ChatGPT.
If you are a manager or a non technical user, you will still benefit from this course by understanding what you can do with ChatGPT.
Join the AI revolution. Don’t wait. Enroll now!
Who this course is for:
This course is great for both technical managers and programmers who want to learn about building ChatGPT apps and RAG based chatbots.
Coding is optional. A knowledge of Python would be required to follow along with the examples.
If you like to code, you will get hands-on experience in building a RAG driven Chatbot.
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