If you've never done any programming courses before, I'd recommend Harvard CS50.
You do need a good amount of math at some point, but there are too many possible math resources to easily include here.
3Blue1Brown's neural networks videos are fantastic introductions to the ideas here. And I hate videos.
Fast.ai has been the go-to starter resource for years. Highly recommended.
MIT's open course is a good survey course that is more theory-oriented.
Huggingface's tutorials are well regarded for a number of specific applied topics.
The Little Book of Deep Learning is the most readable book on the subject, but it's little.
Bishop's Deep Learning comes recommended, extremely comprehensive.
Understanding Deep Learning is also well-regarded, overlaps substantially with Bishop.
Reinforcement Learning: An Introduction is the standard text for the entire area of reinforcement learning, and has limited overlap with other areas.
Programming Parallel Computers covers parallel computing if you are interested in the low-level hardware end of things, and is freely available.
Programming Massively Parallel Processors is similar, probably more comprehensive, and the standard reference book.
this page also mirrored at https://www.verysane.ai/p/learning-ai