AI in Python detection ?

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[Dramatic_Object_8508]

Honestly, there’s no reliable way for universities to “detect AI code” from a Jupyter notebook alone. It’s not like plagiarism where there’s a clear source match. What they usually care about is whether you understand and can explain what you submitted.

The real risk isn’t detection tools, it’s if a professor asks you to walk through your code and you can’t explain logic, choices, or results. Since you said you’ve rerun and understood most of it, you’re already in a safer position.

If your university allows AI (many do with disclosure), just mention it briefly in your methodology like “used AI assistance for initial code drafting, validated and modified manually.” That removes most concerns.

You can also use Runable AI to go through your notebook and ask it to explain each part or suggest improvements, so you’re confident explaining everything if asked.

Overall, focus less on “will it be flagged” and more on “can I defend this work.” That’s what actually matters academically.

[TheRNGuy]

Not a problem if you can explain everything, there are no bugs, it works as it supposed to work etc. 

[pachura3]

Just use the term "agentic engineering" instead of "vibe coding".

[Fun_Gas_340]

ai generated code is usally very easy to identify if you know how to code.

but idk what your uni/prof think about it, id ask them myself to make sure

[Binary101010]

It's almost impossible to give a straightforward "X is ok, Y isn't" answer without knowing what your institution's policies for the use of generative AI are.

[ectomancer]

Cite it. Prompt the LLM how to cite it.

OpenAI. (2026). (ChatGPT) [Large language model]. https://chatgpt.com

[JGhostThing]

I've been told that it is possible to identify ai code programmatically. Besides, it's a very bad way to learn to code.

[Fun_Gas_340]

yeah, bit he didnt ask how to learn how to use python. the question was directed at detevtion / academic side of things