专为开发者设计，从安全连接到成本优化，掌握结构化Prompt工程，打造具备上下文记忆的AI聊天机器人。实战导向，快速落地生产级应用。
原始标题：OpenAI APIs Pro with Python Mega: Build Generative AI Apps
本课程专为开发者打造，是一门跳过复杂理论、注重落地的生产级 Generative AI 开发实战指南。核心内容涵盖使用 .env 保护 API Key 的安全策略、基于黄金框架的结构化 Prompt 工程、精细化成本优化，以及开发具备上下文记忆的企业级客服机器人。您可以从中选择安全连接、JSON 结构化输出或核心项目代码进行深入学习。
Published 8/2026
Created by ACHRAF ER-RAYA
MP4 | Video: h264, 1920×1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 11 Lectures ( 3h 8m ) | Size: 1.7 GB
Build Generative AI applications with Python and the Master OpenAI API, from secure prompts to a working chatbot.
What you’ll learn
⚡ Establish secure connections to the OpenAI API using Python for robust, production-ready AI applications.
⚡ Master prompt engineering frameworks to guarantee predictable, structured JSON outputs every time.
⚡ Calculate token usage and choose the right GPT models to minimize API costs and optimize latency.
⚡ Build and deploy a fully functional, context-aware AI chatbot with persistent conversation memory.
Requirements
❗ Basic understanding of Python programming (variables, loops, basic functions, and API requests).
❗ A free OpenAI account (a small budget of $2-$5 is recommended for hands-on API usage during the course).
❗ No prior machine learning, advanced mathematics, or AI experience is required.
Description
“This course contains the use of artificial intelligence.”
Build a real Generative AI application with Python and OpenAI—without getting lost in machine-learning theory.
This course is for
✨ Python beginners who want a practical GenAI portfolio project
✨ Junior developers building their first OpenAI API application
✨ Data analysts and automation specialists who want to automate text-based work
✨ Freelancers who want to offer AI-powered workflow solutions
✨ Technical creators who want to move beyond manual ChatGPT use
What you will learn
✨ Explain how LLMs and GPT models generate responses
✨ Select a model using quality, speed, and cost criteria
✨ Set up the OpenAI API securely in a Python project
✨ Protect API keys using environment variables
✨ Write prompts with role, task, context, constraints, and output format
✨ Generate structured, reliable AI responses
✨ Build practical text-generation and extraction workflows
✨ Handle common API errors and invalid inputs
✨ Test AI outputs with realistic user scenarios
✨ Build and document a customer-support chatbot portfolio project
Requirements
✨ Basic Python knowledge: variables, functions, packages, and running scripts
✨ A computer with Python installed
✨ An OpenAI API account with available billing or credits
✨ Curiosity and willingness to test, improve, and document your work
Final project
You will build a Python customer-support chatbot that uses approved policy context, returns controlled responses, handles common failures, and includes ten test cases plus a professional README. By the end, you will have a shareable project that demonstrates practical GenAI application-development skills.
Who this course is for
⭐ Python developers and data analysts who want to transition from basic scripting to building intelligent, scalable generative AI applications. It is also highly valuable for tech professionals frustrated by confusing AI documentation who need clear, structured engineering principles to confidently automate workflows and deploy AI features.
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