I recently had someone ask me about a problem in machine learning. The algorithm for it turned out to be something I had read about 30 years earlier, where it was being used to accelerate the simulation of the motion of stars in galaxies. I had never expected to use that algorithm, but its existence, if not details, was there in my long term memory, waiting to surface.

So, I suggest you just read everything you can, getting the gist of things so if you encounter something similar you know where to look.

I also suggest looking for little tricks you can apply again and again. For example, some of the data structures in that course use a trick where you break the structure into a top part, using one algorithm, and a bunch of leaf parts, each of size maybe O(log n), that are handled using another algorithm. Often this combination does better than either algorithm by itself.