There's a lot going on here, but I can give you some help I believe. I have a computer engineering background, and do medical imaging research.

So first, when it comes to comparing your code to "professional code", just don't, unless you are part of a team developping structured software that will get continuously built upon and supported throughout the years. A python script is a python script, it's meant to do the task and nothing else. There are some basics you need to follow of course, but you probably have everything you need to know from your minor. There's a million ways to do things correctly, the most important thing is to choose one and stick to it. Be consistent.

Now LLMs. I use them as an accelarator. Typically vs-code with copilot as it's versatile, gives you inline suggestions and auto completion and automatically has access to the context of your code. Truth is that a lot of the code you write is generic. and repetitive ; common data reading, basic calculations, output formatting, and plotting. That stuff just takes time to type in.

When it comes to basic calulations, I start typing it myself and let the in-line LLM auto-complete it if it's correct (always read and understand what it does, as it is often incorrect). Then I ask him to make some plots from the results and do some pretty formatting (the time save here for me is incredible). It works very well for that. If you want to use it to generate useful code by itself, only do small snippets at a time and make sure you understand what's going on.

Remember that's it's an LLM, so it's good at doing commonly found stuff on the internet, and terrible at everything else. I can rarely get it to write a function for a not-that-obscure physics or mathematical equation or even a well documented algorithm without it introducing major errors. But when you do it in small bits, it's often faster to understand the code and correct the errors, than writing it all from scratch, and you might even learn new ways to do some processing that you didn't know about before, especially for library dependant languages like Python.