Depends what you’re trying to learn, and how much of a beginner you are. If you want to learn the shell, try the Software Carpentry tutorials:

• The Unix Shell - Software Carpentry
• Version Control with Git

If you know the basics, you might try honing your skills with CLI Mystery (murder mystery puzzle).

You’ll probably want to learn how to use the following:

• SSH
• Command-line text editor. Choose one of the following:
  • Nano <- Smallest learning curve
  • Vim (or Neovim) <- My favourite (See Mastering the Vim Language)
  • Emacs <- Some people like it

The final tip is: It’s usually better in the long run to spend 2 hours reading the documentation than 2 minutes searching the web. Reading the documentation helps you to understand the big picture, and gives you a much better foundation. Of course, if you’re reading the documentation and don’t understand something, searching the web is an OK way to figure it out.

Tax-deductible donations get you part way there.

Don’t forget apk! It’s FAST!

What are your hobbies? Most people struggle to learn programming until they find a project that they are interested in. You mentioned an interest in music. Perhaps you could try Sonic Pi, which is a live coding environment where you can create music from code. It comes with a built-in tutorial, and a bunch of pre-written example code-music. It’s built with the ruby language.

I’d suggest maybe stick with Godot 3 until 4.1 comes out. I just started playing with 4, and hit a bug where Godot will hard crash whenever you try to view the Terrains tab if you’ve created terrain sets, used them in your scene, then deleted the terrain sets.

Also, Godot 4 doesn’t have as good support for older systems due to the new Vulkan backend. I worked around this by switching to the mobile renderer which works better on my old hardware.

Can I suggest duckdb? You can start out writing SQL directly on top of CSV and Parquet files. But then if you want/need to do something more complicated, you can import duckdb into Python, keep running the SQL you already wrote, convert it to a Pandas or Polars dataframe, transform it, then query the result in SQL.