3 hours agoIT & SoftwareLearn how to verify, debug, and safely deploy code created with AI tools like ChatGPT, Copilot, and Replit AI
Course Description
AI coding tools can dramatically speed up development, but they also introduce hidden bugs, incorrect assumptions, and risky code that can break your application if not properly tested.
In this course, you’ll learn how to systematically test, debug, and validate AI-generated code so you can use tools like ChatGPT, GitHub Copilot, and Replit AI with confidence.
Instead of blindly trusting AI outputs, you’ll develop a professional workflow for catching errors early, verifying assumptions, and preventing costly mistakes.
What you’ll learn:
How AI coding assistants make mistakes (and why)
How to detect hallucinated APIs, outdated code, and wrong assumptions
A step-by-step workflow for debugging AI-generated code
How to test AI code using unit tests, integration tests, and manual validation
How to write better prompts to reduce errors upfront
How to safely refactor and improve AI-generated code
Common AI coding pitfalls across frontend, backend, APIs, and databases
How to verify AI outputs before deploying to production
Who this course is for:
Developers using AI coding tools like ChatGPT, Copilot, or Replit
Beginners learning to code with AI assistance
Professionals who want to avoid bugs and production issues
Anyone using “vibe coding” workflows and wants to make them reliable
Why this course matters:
AI is a powerful coding assistant, but it’s not always correct.
The difference between amateur and professional use of AI tools is verification and testing.
By the end of this course, you’ll know how to:
Trust AI when appropriate
Question it when necessary
And catch errors before they cost you time, money, or reputation
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