https://teachyourselfcs.com . I have read few books from the list and found it to be comprehensive as well as manageable. The courses and books have been selected so that one can study it outside of regular university course. Books are self contained and full with exercises. It can easily take 1-2 years of serious effort to get through the material.

The Stanford cryptography class (http://crypto.stanford.edu/~dabo/cs255/) and associated book (https://crypto.stanford.edu/~dabo/cryptobook/BonehShoup_0_4....) is almost everything you'd ever want to know about cryptography. If you really like that and want to see the frontiers of cryptography research, the next (and last!) class is https://crypto.stanford.edu/cs355/23sp/; alternatively, there's a security class (https://cs155.stanford.edu/) more focused on industry and application.

Pro tip: nearly every instance of both these classes is available online (all the way back to 1998!), so if something's not making sense, you can always go back and see if it was explained differently in a prior iteration of the class.

From Nand to Tetris: Build a Modern Computer from First Principles https://www.coursera.org/learn/build-a-computer

Phenomenal look at different systems involved in a computer, and has you build simple versions of logic gates, ALU, assembler, compiler, bootloader, and graphics engine. Highly recommend for folks who didn't study CS in school.

https://www.csunplugged.org/en/ is pretty nice for computational thinking

teachyourselfcs is a perfect recommendation as it doesn't include a ton of links thus resulting in analysis paralysis.

https://www.notion.so/wdesert/Curated-Resources-e37b0646f3f1...

This is a list I maintain for myself. It's more about general software development and is not as structured and focused as teachyourselfcs, but you mind find something useful in it

https://craftinginterpreters.com/

Base your studies on Teach Yourself CS. If you finish one item from each of their courses you will be more knowledgeable than even many CS graduates. If you could finish every book and video series they recommend for each course you would be reasonably well prepared for amateur research.

https://teachyourselfcs.com/

Cornell CS 3110 - OCaml, lectures on YouTube https://www.youtube.com/playlist?app=desktop&list=PLre5AT9Jn...

The quintessential 0 to 1 CS course with amazing teacher and tools to get you started. Also has marked tests to help you learn.

https://cs50.harvard.edu/x/2023/

CS50 hasn't been mentioned yet: https://pll.harvard.edu/course/cs50-introduction-computer-sc...

Great intro to CS.

I have learned a tremendous amount about Linux and DNS and general computing from Julia Evans' zines and her blog. She's also a big fan of "programming playgrounds" [0] or interactive teaching tools.

[0] https://jvns.ca/blog/2023/04/17/a-list-of-programming-playgr...

While it may not be the _best_ this book is available from the author online.

Elaine Rich's textbook "Automata, Computability and Complexity: Theory & Applications" https://www.cs.utexas.edu/~ear/cs341/automatabook/index.html

Useful because it covers non-deterministic Turing Machines complexity classes like BPP,ZPP,RP,etc.. that you would run into Monte Carlo methods etc. As the only Non-deterministic Turing machine most people have been introduced to is the maximally lucky guesser from NP's definition it can help with practical solutions.

Unfortunately it doesn't have bounded-error quantum polynomial time (BQP) which would help set expectations for quantum supremacy.

All of Beej's writing is very informational. I especially enjoyed his guide to C, although his guide to network programming is more well known.

https://beej.us/guide/

Neural Networks: Zero to Hero, by Andrej Karpathy [0].

[0] https://www.youtube.com/playlist?list=PLAqhIrjkxbuWI23v9cThs...