As I'm learning Python this time around it is with the purpose of being able to understand and complete some AI projects.
This is the first thing that helps. Have a clear goal/endpoint in mind. What is it you want to be able to do or build?
I have tried a bunch of resources over the years for learning Python. I never got too far because I didn't have a clear goal, and I was more focused on web development.
I am now using Kaggle, for reasons explained in the above link. It is specifically geared towards Data Science/Machine Learning, so it makes a lot of sense to do their courses, as it segues right into the sort of projects I want to be doing.
Just now I have been doing the Python mini-course, and at a certain point the tutorial didn't make sense to me. The first instinct is to assume:
"Well, this tutorial is obviously BS. What idiot wrote this? It's clearly not simple and obvious enough."
OR
"Well, I'm obviously super dumb I need some baby-style Python-by-numbers tutorial."
But I carried on through the tutorial and came back to that part and went over it again. Instantly it was all pretty clear and made sense the second time round.
It made it easier because I have definitely decided Kaggle is the way I'm going. So I kept confidence it was the right thing, and looking for something else wasn't a consideration.
Perhaps at these points we'd be tempted to assume this tutorial 'just isn't right for me', or 'I bet I can find one that explains things better.'
But, in the end, as long as you get a course that is well regarded it'll probably be fine. There will of course be variance in clarity and styles. But there will be trade-offs in all tutorials, documentation, and educational courses.
The moral of the story is pick your resource and stick with it (that's not to say don't do a bit of vetting and trialling early on).
In most cases you'll learn more struggling when you don't understand part of the tutorial than jumping ship to the next one.
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