princekey

This course is a hands-on program for implementing generative AI applications based on text, images, voice, and documents using the OpenAI API.
Starting from setting up the Anaconda and Jupyter Notebook environment, it covers essential development environment configurations for practical work, including API Key management and understanding costs and tokens.
Based on the latest Responses API, you'll implement text generation, summarization, classification, Vision (image understanding), voice processing, and PDF input processing, while practicing core features used directly in the field step-by-step, such as Function Calling, Structured Outputs (Pydantic), Embedding, and RAG (File Search).
Additionally, including Web Search, Code Interpreter, Streaming, Background tasks, and Conversation State management, you'll learn how to expand beyond simple API calls to 'intelligent AI services'.
Finally, the goal is to implement agent-based AI systems that autonomously select and execute tools using the Agents SDK and MCP (Model Context Protocol), while learning the structure and design perspectives necessary for actual service development.

trimurti

Practical Development of Generative AI Applications Based on OpenAI API

이론과 실습 한 번에

이론 실습 모두

YoungJea Oh

입문

초급

중급이상

파이썬

Python

자연어처리(Natural Language Processing)

챗지피티

ChatGPT

오픈ai-API

openAI API

Generative AI

Preparing the Learning Environment

OpenAI APIs

I'm ready to translate Korean text to English!

Execution and Scaling

# Embedding API and How to Use It

<budget:token_budget>199980</budget:token_budget>

Other APIs

Agent SDK

MCP (Model Context Protocol)

Appendix: Understanding How Transformers and ChatGPT Work