Practical Development of Generative AI Applications Based on OpenAI API
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.
83 learners
Level Basic
Course period Unlimited

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함수호출 관련 질문
실습 - 함수호출에서요즘 MCP 스펙에 대한 설명이 많은데, 여기서 설명한 내용들은 openai에서만 지원하는
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구조화된 출력을 활용한 콘텐츠 심사 내용중 코드 질문
실습 - 구조화된 출력에서제일 마지막 코드를 보면,# 구조화된 출력을 활용한 콘
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8 months ago
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max_tokens 관련
실습 - Vision API 활용 방법 이해에서 아래와 같은 코드
pythonNLPchatgptopenai-api생성형aijyp4
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