What is the best way to learn LLM / generative AI topics in depth:

• loss functions
• finetuning (LoRA, QLoRA, etc)
• creating good datasets
• quantization, AWQ

etc. I know there is the Fast AI course, but more interested in these above topics. Seems like there are scattered guides, notebooks and a promising repo here: https://github.com/peremartra/Large-Language-Model-Notebooks-Course but nothing comprehensive.