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Testing AI Code From ChatGPT Or Replit AI (Vibe Coding)
Rating: 4.4 out of 5(17 ratings)
879 students

Testing AI Code From ChatGPT Or Replit AI (Vibe Coding)

Learn how to verify, debug, and safely deploy code created with AI tools like ChatGPT, Copilot, and Replit AI
Created byAlex Genadinik
Last updated 5/2026
English
English [Auto],

What you'll learn

  • Understand how AI coding assistants make mistakes (and why)
  • Write better, and more bug-free software
  • Spend less time debugging by anticipating potential pitfalls
  • Become more proficient with vibe coding and AI coding assistants like Replit, Lovable, or Base 44
  • Launch better products
  • Decrease your frustration when dealing with AI, and ensure more correct outputs
  • Learn about AI errors like AI confabulation, AI temporal drift, AI knowledge cutoff problem, AI stale knowledge.

Course content

7 sections • 14 lectures • 55m total length

  • Introduction and welcome3:08

    Learn to test ai code professionally with test cases and test plans, and master debugging while understanding ai processes to prevent errors from insufficient context or assumptions.

Requirements

  • There are no prerequisites for this course, just a love for learning, and an open mind.

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  • How to detect hallucinated APIs, outdated code, and wrong assumptions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

Who this course is for:

  • Enginners
  • Vibe coders
  • Entrepreneurs who are building things with AI

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