Same background here. I finally got into stochastic calculus last year thanks to a local college course (after several unsuccessful attempts on my own).
You need at least
1. a basic grasp of classical calculus, measure theory and topology
2. solid understanding of probability theory
3. basics of stochastic processes
I believe you should be able to dive in from there. It's good to have an idea where you're heading as well (mathematical finance and modelling and pricing derivatives? Bayesian inference and MCMC? statistical physics?).
Practice a few polyrhythms, get used to things like:
X . X X X . X . X X X .
A . . A . . A . . A . .
B . B . B . B . B . B .
and:
X . . X . X X X . X X . X . X X . . X . X X . . X X . X X . X . . X . X X . . X X . X . . X . . X X X X . . X X X X . . X . . X . X X . . X X . X . . X . X X . X X . . X X . X . . X X . X . X X . X X X . X . .
A . . . . A . . . . A . . . . A . . . . A . . . . A . . . . A . . . . A . . . . A . . . . A . . . . A . . . . A . . . . A . . . . A . . . . A . . . . A . . . . A . . . . A . . . . A . . . . A . . . . A . . . .
B . . . . . . B . . . . . . B . . . . . . B . . . . . . B . . . . . . B . . . . . . B . . . . . . B . . . . . . B . . . . . . B . . . . . . B . . . . . . B . . . . . . B . . . . . . B . . . . . . B . . . . . .
C . . C . . C . . C . . C . . C . . C . . C . . C . . C . . C . . C . . C . . C . . C . . C . . C . . C . . C . . C . . C . . C . . C . . C . . C . . C . . C . . C . . C . . C . . C . . C . . C . . C . . C . .
Learn to do them with one limb (or finger) per line, and also with all the lines on the same limb (or finger). And then suddenly, they'll start to feel intuitive, and you'll be able to do them by feel. (It's a bit like scales.)
Of course, getting a computer that's useful in practice out of this would require some thought.
A simple model: you could only allow programs written in Coq (or similar), ie progams that come with a proof of termination (or a slight generalisation, that allows for infinite event loops, as long as each run threw the loop behaves well, in some sense).
There's a trivial escape hatch, where you just take your normal unproven program but forcefully terminate it after 2^64 steps. That's strictly speaking not Turing complete, but you wouldn't be able to tell the difference during the lifetime of the computer.
Perhaps I belong to the minority, but I really don't think about containers as Docker. Actually, I don't remember the last time I used Docker for anything. For the past several years, I've been using either Podman or systemd-nspawn, as yourself.
You need at least
1. a basic grasp of classical calculus, measure theory and topology
2. solid understanding of probability theory
3. basics of stochastic processes
I believe you should be able to dive in from there. It's good to have an idea where you're heading as well (mathematical finance and modelling and pricing derivatives? Bayesian inference and MCMC? statistical physics?).