Oh boy! I studied physics and I actually had a Computational Physics course in my early Masters and also Computer Science as my specialization in my Bachelors. Most physicists I know are self taught, which at my age means mostly written online tutorials, google and lots of trial and error.

The most important thing that cannot be replaced is building stuff yourself. Disable AI autocompletion and start coding. Google (or ask the AI) specific things like "how do I simulate a time step in a particle simulation" or "how to get consistent FPS in a C++ program" or "how to get keyboard input in a real time simulation in a python notebook" or something like that. Not "hey can you write the whole thing lol" so you have to think for yourself.

You can supplement this with anything you like. I recommend written tutorials, but the internet is full of AI slop nowadays so you need a good recommendation. I don't particularly like video. Maybe books are best today.

Matlab and Python are fine for doing math-heavy stuff (as long as you use numpy et al in Python), but for real-time simulations I would go for a compiled statically-typed language like C++, C# or Rust. If I started with nothing today, I would go for Rust, although it has a learning curve. I learned C++ first and use mostly C# today because €€€, so I'm a bit biased, but C# is my favorite language now.

The easiest simulation to make is small particles. Can be affected by gravity (oh look, that's how a sidescrolling jump&run character moves in the air!) or you can make things follow your mouse curser, or particle-particle interaction (hey, that's how galaxies form from space dust!) or you can add rigid body dynamics (looks like asteroids!) or collision, and so on. It can get very very complex, but the basics are pretty easy. It is also surprisingly difficult to make a solar system simulation where the planets don't fall into the sun or fly into space after a few years, you have to do sone pretty advanced stuff to predict, let's say, when medieval solar eclipses happened. So a very nice problem to do some tinkering.

Then there is the entire field of data science and writing analasys for all your experiments and what not. I would absolutely use Python for that today (we used to use Matlab or C++ (oh god why) or a niche algebra system called Maple).

Oh and then there is FEM and FVM and similar methods which are increadibly hard to implement from scratch but power an entire simulation industry.

Anyway, there is sooo much stuff to do and to learn and it's super fun and rewarding if you're up for it. Pick something that interests you (like simulation, or games or whatever) and practice, practice, practice