Are math skills really? Most aspects of deep learning don't require a deep understanding of mathematics to understand. Backprop, convolution, attention, recurrent networks, skip connections, GANs, RL, GNNs, etc. can all be stood with only simple calculus and linear algebra.

I understand that the theoretical motivation for models is often more math-heavy, but I'm skeptical that motivations need always be mathematical in nature.