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Notes -
So how is the best way to teach data structures, algorithmic complexity, single responsibility, patterns, (more things which are not programming) etc.?
The most ubiquitous data structures and algorithms are really simple to understand. Well over half of programming with ds is sticking a bunch of primitives into a struct, giving it a name, and keeping track of a list of them (or a list of refs to them). Things like "single responsibility" and "patterns" more generally are already getting into territory that I deem to be fashion. To the extent that those ideas are useful they're trivial, and they go much beyond the point of useful in their prescriptions.
Complexity is also pretty easy to teach by just making people perform different algorithms with pen and paper so they can feel the difference between them. From that intuition it's not difficult to understand how different algos can be a better/worse choice depending on the size of your dataset. But this can also be misleading, so I would include a section on how to test these things in the real world.
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