If you must...
Coding is a side benefit to the way we want to use Jupyter. It is not the primary reason that this is a useful tool. In most cases we are using jupyter's code cells (assumed to be running python) as calculators. Extensive use of the numpy library is used precisely so we can avoid having to 'loop' over elements and not have to learn the intricacies of data structures. That being said, some coding skill is helpful as we develop models for physical phenomenon. Knowing how to build functions and how conditional branching works helps make things go more smoothly. Keep in mind that the materials here are not presented as a 'coding' course. There are many excellent online resources for that. This is just a quick set of guides to help fill out the details of what we want to do.
The structure of this folder is a graduated set of interactive lessons to get a student started in the practical elements of the python language. As such, each 'chapter' is intended to work in sequence from basics to ever increasing sophistication.
Skipping steps means the reader is taking responsibility for what was covered earlier. Some people are fine with this. I would caution about skipping too much. Just as learning a native tongue as we grow up through application and inference leaves gaps in our understanding of the formality, learning a programming language solely through example can leave blind spots. It pays to at least skim the prior material.