Testing and Quality Assurance

An AI can write a hundred lines of plausible code in seconds. That is the promise, and it is also the problem: plausible is not the same as correct, and you cannot read every line closely enough to be sure. Tests are how you know. They are the reason you can accept AI code quickly and still sleep at night.

Testing and Quality Assurance teaches you to build that safety net. You will learn what a test actually is and why it matters more when an AI writes the code, how to get an AI to write good tests for you, which edge cases everyone forgets, why coverage is not the same as confidence, and how to run your checks automatically on every change so a break is caught in seconds rather than by a customer. You finish by planning a tested, green project of your own.

No testing background is needed, and it is tool-agnostic. Everything is taught in plain language with clear diagrams and small examples. Each module blends a short video overview, illustrated lessons, a knowledge-check quiz, and a hands-on interactive activity, including a red-to-green test run you drive yourself.

What you will be able to do:

• Explain why tests matter more, not less, when an AI writes the code.
• Read and write a test in the arrange, act, assert shape.
• Ask an AI for tests that check behaviour rather than implementation.
• Cover the happy path, the edges and the errors, including the cases everyone forgets.
• Understand why high coverage can still mean low confidence.
• Run checks automatically on every change, and keep your project green.

Who it is for: Anyone building with AI who wants to ship with confidence instead of hope. Especially useful straight after learning to debug.

Course outline: Orientation · Why Tests Matter More with AI · Getting AI to Write Tests · Coverage and Edge Cases · Continuous Checks · Capstone: A Tested, Green Project.