| File Name: | Prompt Engineering with Python & OpenAI (ChatGPT) API |
| Content Source: | https://www.udemy.com/course/prompt-engineering-with-openai/ |
| Genre / Category: | Programming |
| File Size : | 2.2 GB |
| Publisher: | Scott Barrett |
| Updated and Published: | March 20, 2026 |
This course is for Python developers who want to build real AI applications using the OpenAI API — not just use ChatGPT in a browser. You’ll work directly with OpenAI’s modern Responses API — the one OpenAI recommends for new projects — through 25+ hands-on Jupyter notebooks with working code you can run and reuse immediately.
Prerequisites: Basic Python familiarity — classes, functions, loops, and importing packages. Environment setup is covered in Module 1.
What You’ll Learn:
- API Fundamentals Connect to the OpenAI API, configure your environment, and make your first calls using the Responses API. Understand model selection, token usage, and cost tracking from day one.
- Prompting Techniques Master zero-shot, one-shot, and few-shot prompting. Build structured JSON outputs for reliable parsing, design role-based personas, create reusable prompt templates, and evaluate prompt quality systematically.
- Production Patterns Handle API errors with exponential backoff, manage rate limits, track token usage and costs with tiktoken, cache responses to eliminate redundant API calls, and manage context windows for long conversations.
- Function Calling Connect the AI to external tools and APIs using OpenAI’s function calling workflow. Build assistants that look up live data, query real databases, and take actions in the world.
Capstone Projects
You’ll build three capstone projects that combine everything you’ve learned into real, deployable applications.
- Research Assistant — Decomposes complex questions into sub-questions, investigates each one independently, and synthesizes the findings into a structured answer.
- Production Support Bot — A fully functional support chatbot with budget controls, sliding window context management, and response caching. Built across two modules to show how production systems are assembled incrementally.
- Multi-Tool Agent — Connects to a live weather API and queries a real SQLite database using function calling. Demonstrates how AI can interact with the outside world through Python functions.
What You’ll Walk Away With
25+ tested Jupyter notebooks, reusable helper functions, and production-ready patterns you can drop into your own projects immediately.
DOWNLOAD LINK: Prompt Engineering with Python & OpenAI (ChatGPT) API
Prompt_Engineering_With_Python_Openai_Chatgpt_Api.part1.rar – 1000.0 MB
Prompt_Engineering_With_Python_Openai_Chatgpt_Api.part2.rar – 1000.0 MB
Prompt_Engineering_With_Python_Openai_Chatgpt_Api.part3.rar – 286.3 MB
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