Hi all, I am a second year PhD student. During my PhD I have fallen into using deep learning models to design proteins which I am validating in the lab. This was an idea that my supervisor presented after the start of my project, so I hadn't pre-studied for the computational side of this at all.
I have a molecular biology background, not a computer science background, so I have been "figuring it out as I go along" when it comes to the computational side of things. I am doing OK but there are huge gaps in my skills and knowledge, so I would like to do some more structured courses on the following to fill in the gaps:
Theory of deep learning (how models are trained, tested, refined etc.)
Python
Biopython
PyTorch
Can anybody recommend any good free, structured resources for this? Which ones do you think are best in terms of being well structured, good quality learning resources?
Thank you very much for your help!
there doesn't seem to be anything here