Prompt Engineering: Build AI Apps with OpenAI (ChatGPT) | Udemy [Update 04/2026]
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Genre: eLearning[/center]

What you'll learn:
[list]
[*]Connect to the OpenAI Responses API and make your first live API calls from Python
[*]Build structured JSON outputs that return reliable, parseable results every time
[*]Handle API errors gracefully using exponential backoff and rate limit strategies
[*]Design reusable prompt templates with roles, instructions, examples, and output format controls
[*]Track token usage and costs in real time using tiktoken and the API usage object
[*]Implement response caching and context window strategies for production applications
[*]Connect the AI to external tools and databases using the complete function calling workflow
[*]Build three real AI applications - a Research Assistant, Production Support Bot, and Multi-Tool Agent
[/list]

The API is where _real_ applications are built. This course is how you get there.

This course is for developers who are ready to move from experimenting with AI to actually building with it. You'll work directly with OpenAI's modern Responses API - the one OpenAI recommends for all new projects - writing real code that connects to real tools and produces real results.

WHAT YOU'LL BUILD

You'll complete Three Capstone Projects
, each one closing out a module after the concepts that make it possible have been taught.

_Research Assistant_
- Decomposes complex questions into sub-questions, investigates each one independently, and synthesizes the findings into a structured answer. Built using instruction chaining, personas, and advanced few-shot techniques.

_Production Support Bot_ - A fully functional support chatbot with budget controls, sliding window context management, and response caching. Built incrementally across two modules to show how production systems are actually assembled - not just demonstrated in a single notebook.

_Multi-Tool Agent_ - Connects to a live weather API and queries a real SQLite database using function calling. This is AI that interacts with the outside world through Python functions.

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.

_Core Prompting_
- Zero-shot, one-shot, and few-shot prompting. Understand exactly how the model responds to different prompt structures and w***t matters.

_Production Prompting_ - Structured JSON outputs for reliable parsing, error handling with exponential backoff, reusable prompt templates, and systematic prompt evaluation so you can measure whether your prompts are actually working.

_Advanced Prompting_ - Instruction chaining, role-based personas, advanced few-shot techniques, and self-consistency strategies for more reliable outputs.

_Production Patterns_ - Token counting and cost tracking with tiktoken, context window strategies for long conversations, and response caching to eliminate redundant API calls.

_Function Calling_
- The complete function calling workflow. Connect the AI to external tools, live APIs, and real databases so it can take actions in the world.

HOW THE COURSE IS STRUCTURED

Six modules. 25+ hands-on Jupyter notebooks. Each concept is taught in its own notebook with working code you can run, modify, and reuse. Each module closes with a capstone that puts everything you just learned into a real, deployable application.

PREREQUISITES

Basic Python familiarity - classes, functions, loops, and importing packages. Environment setup is covered in Module 1.

You'll also need an OpenAI account with a minimum of $5 in API credit. That's more than enough to complete every exercise in the course using gpt-5-mini, the default model used throughout.

WHO THIS COURSE IS FOR

Engineers adding AI capabilities to existing applications. Analysts automating workflows with Python. Technical leads evaluating how to integrate AI into their teams' work.

WHO THIS COURSE IS NOT FOR

Complete beginners to Python. If you're new to Python, build that foundation first - you'll get significantly more out of this course when you come back.

Who this course is for:
Python developers who want to build real applications using the OpenAI API
Engineers adding AI capabilities to existing products or workflows
Technical leads evaluating how to integrate AI into their teams' projects

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