Author here. Text is not AI-generated or AI-assisted in any way. It's a collection of great learning resources I have cultivated over multiple years, recently even removed something from the list.
Take the hint: your slop hero image is damaging the rest of your page by association. If you don't want people to assume your page is garbage, don't lead with garbage.
I'd add to the Money Stuff newsletter the Money Stuff podcast, with Matt and Katie Greifeld (BBG reporter). The two have great chemistry, and slightly different interests in finance, so it covers topics beyond the single thread he typically covers in the newsletter.
- Skill: Git, covering both high-level aspects (commiting, branching, GitHub/GitLab, etc) and its internals (objects, references, packfiles, protocols, etc)
- Kind of material: free e-book, book and website
- Why is it good: easy to read, even when approaching the inner aspects. It's very unlikely that you won't learn something new and amazing after reading it. The Git internals chapter is a gem, providing and demonstrating the plumbing commands that manipulate the internal data structures.
- Why is it good: covers the language and functional programming in a very fun and informal way. Reading it and learning Haskell made me a better programmer in other languages (specially in Python and Kotlin)
- Why is it good: covers the x86-64 assembly using the NASM syntax, explaining the basic instructions, the stack, function calls, syscalls and so on. Easy to read, with some exercises. The chapters themselves are valid NASM code that you can assembly and run in your machine.
- Why is it good: explain what happens when you run a program, covering syscalls, multitasking, memory management, fork, exec, ELF and so on. Everything written in a very fun and informal way
5. Fluent Python by Luciano Ramalho
- Skill: Python, but for those who already know Python and want to improve their skills
- Kind of material: book
- Why is it good: explains in depth several Python concepts, sometimes even showing the bytecode.
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[ 4.6 ms ] story [ 60.4 ms ] threadThe image is AI generated.
The text is not AI generated.
1. Pro Git, by Scott Chacon and Ben Straub (https://git-scm.com/book/en/v2)
- Skill: Git, covering both high-level aspects (commiting, branching, GitHub/GitLab, etc) and its internals (objects, references, packfiles, protocols, etc)
- Kind of material: free e-book, book and website
- Why is it good: easy to read, even when approaching the inner aspects. It's very unlikely that you won't learn something new and amazing after reading it. The Git internals chapter is a gem, providing and demonstrating the plumbing commands that manipulate the internal data structures.
2. Learn you a Haskell for Great Good by Miran Lipovača (https://learnyouahaskell.com/)
- Skill: Haskell
- Kind of material: free e-book, book and website
- Why is it good: covers the language and functional programming in a very fun and informal way. Reading it and learning Haskell made me a better programmer in other languages (specially in Python and Kotlin)
3. intro_x86-64 by Luana Martins (https://gitlab.com/luamfb/intro_x86-64)
- Skill: x86 assembly (NASM)
- Kind of material: tutorial mixed with code
- Why is it good: covers the x86-64 assembly using the NASM syntax, explaining the basic instructions, the stack, function calls, syscalls and so on. Easy to read, with some exercises. The chapters themselves are valid NASM code that you can assembly and run in your machine.
4. Putting the you in CPU by Lexi Mattick (https://cpu.land/)
- Skill: operating systems and program execution
- Kind of material: website
- Why is it good: explain what happens when you run a program, covering syscalls, multitasking, memory management, fork, exec, ELF and so on. Everything written in a very fun and informal way
5. Fluent Python by Luciano Ramalho
- Skill: Python, but for those who already know Python and want to improve their skills
- Kind of material: book
- Why is it good: explains in depth several Python concepts, sometimes even showing the bytecode.