Resources please

Hi, I am working in the deep learning space but my niche domain has meant that all of my work has been fully focused on pretraining. I have learnt a lot here and feel like I have a good understanding of deep learning, although I know I must be missing so much as I’ve never touched RL. But now I want to!

I occasionally come across papers and posts that discuss DPO, GRPO, etc. and have an extremely constrained knowledge of value iteration, q learning, etc. but now I want to start understanding all the methods better, which methods work on which types of tasks and most importantly why.

Preferably I’d like a mix of both the theory and practical resources. Please can you help me out!