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OpenAI API for Python Developers

Via LinkedIn Learning

LinkedIn Learning based on 157 ratings

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Overview

This technical course teaches Python developers how to integrate Open AI’s API into their applications. Learners explore API authentication, prompt design, managing conversations, and deploying AI-powered features like chatbots and content generation. The curriculum includes hands-on coding exercises to build practical AI functionalities. Developers gain the skills to leverage Open AI’s powerful language models within Python ecosystems efficiently.

Syllabus

Introduction
  • AI integration with Python
1. Introducing Generative AI: What You Need to Know
  • Generative AI: The future of development
  • Generative AI: Genesis and evolution
  • What you should know
  • What tools you need
2. Generative AI: The Key Concepts and Getting Started
  • Getting started with OpenAI: Create an account
  • Getting started with OpenAI: The key concepts
  • Start a new project: Quickstart
  • Configure the project: Set up an API key
  • Defining prompts and making requests
3. ChatGPT API: Build a Chatbot Application
  • Introduction to conversational AI
  • Project setup and overview
  • Authentication and configuration
  • Define a system message with instructions
  • Making requests and generating chat completions
  • Challenge: Create a funny chatbot
  • Solution: Create a funny chatbot - part 1
  • Solution: Create a funny chatbot - part 2
4. Experimenting with Other Generative Models
  • Introducing the Moderation API
  • Add a moderation layer
  • Text to image: Introducing the DALL·E model
  • Generate creative art with DALL·E
  • Create an image gallery with DALL·E
  • Whisper Audio API: Speech-to-text
  • Whisper Audio API: Transcribe audio samples
  • Whisper Audio API: Translate audio sample
5. Extending the LLM Capabilities with Function Calling
  • Introduction to OpenAI function calling
  • Define functions and parameters
  • Call functions
  • Challenge: Connect to a public API
  • Solution: Call functions and generate extended responses
6. Building a Custom-Knowledge Chatbot with LangChain, Embeddings, and ChromaDB
  • Getting started with LangChain
  • LangChain key concepts
  • Chain components (LCEL)
  • Load and split documents
  • Create a vector store and embeddings (Chroma)
  • Run chains: Knowledge retrieval and content generation
  • Create a user interface with Streamlit
Conclusion
  • Last words and next steps
OpenAI API for Python Developers
Go to Class

via LinkedIn Learning

2 hours 18 minutes

Certificate Available

English

On-Demand

Instructor

Sandy Ludosky

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