HN Explorer

Can we create a thread for some of the best materials on CS available online?

173 points by ggr2342 ↗ HN
This thread may prove helpful for someone wanting to study some topic in Computer Science on their own if it becomes well populated.

What are some of the best materials (courses, books, notes, video talks, etc) on any CS/programming topic that you have gone through or know of?

Also mention a bit about why it is useful.

49 comments

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ipnon
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/

blintz
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.

pushpankar
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.
hirvi74
> It can easily take 1-2 years of serious effort to get through the material.

Still faster than my CS degree.

xwowsersx
Is the recommendation to do the book AND the related video course for each subject or it's either or..? Or use the video course as needed if/when the book isn't enough?
xwowsersx
Doh, it says right there: "using either the suggested textbook or video lecture series, but ideally both" :)
dondraper36
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

jamestimmins
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.

hirvi74
I have been considering going through this book/program myself. I do have a CS degree, but I really need to brush up on somethings, and I will imagine I will learn a lot of new things too.

However, I noticed there are two versions of the book. Do you think the version matters?

jamestimmins
The book (and course, IIRC) is split across two books. The first one focuses on the lower level systems, and I believe the seconds one deals with the bootloader, language implementation, screen animation, and building the game.

It doesn't look like there are multiple versions of the books, unless I'm missing something. I did the two versions of the course without the book, and really enjoyed both. Although the writers of https://teachyourselfcs.com/ only recommend the first one, so it depends what you want to get out of it and whether the approach resonates.

vmilner
There are two editions of the book.
nyrikki
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.

wwarner
this isn’t nearly as comprehensive, but Michael Collins’ notes on machine learning for NLP are really succinct and IMO intuitive

http://www.cs.columbia.edu/~mcollins/

(search for notes, where he’s listed links to pdfs he uses in classes)

sn9
Lots of great suggestions here.

I'll throw out a recommendation for The Little series of books (e.g., The Little Schemer, The Seasoned Schemer, The Reasoned Schemer, The Little Typer, etc.)

The first book is all you need to grok recursion. You can just toss a copy at any student who struggles with it.

The second book ends with some really non-trivial CS stuff.

They're fantastic examples of the power of good pedagogy to explain interesting and difficult concepts normally relegated to drier texts.

Al0neStar
# Programming

"A Data-Centric Introduction to Computing"

https://dcic-world.org/

# Programming Language Theory

"Programming Languages: Application and Interpretation"

https://www.plai.org/

"Crafting Interpreters"

https://craftinginterpreters.com/

# Algorithms/Data Structures

* Pure C *

"Algorithmic Thinking: A Problem-Based Introduction"

https://nostarch.com/algorithmic-thinking-2nd-edition

# Competitive Programming/Interviews

"Competitive Programming book, 4th edition (CP4)"

https://cpbook.net/

"Elements of Programming Interviews in Python"

http://elementsofprogramminginterviews.com/

# Compilation

"Essentials of Compilation: An Incremental Approach in Python"

https://github.com/IUCompilerCourse/Essentials-of-Compilatio...

# Database Systems

"CMU: Intro to Database Systems"

https://15445.courses.cs.cmu.edu/

"CMU: Advanced Database Systems"

https://15721.courses.cs.cmu.edu/

# Calculus I/II & Real Analysis

"A Course in Calculus and Real Analysis"

https://link.springer.com/book/10.1007/978-3-030-01400-1

"A Course in Multivariable Calculus and Analysis"

https://link.springer.com/book/10.1007/978-1-4419-1621-1

# Physics

"Matter and Interactions"

https://matterandinteractions.org/

# Linear Algebra & ML

* A Series of books by prof. Joe Suzuki without using any external library for the implementations *

"Statistical Learning with Math and Python"

https://link.springer.com/book/10.1007/978-981-15-7877-9

"Sparse Estimation with Math and Python"

https://link.springer.com/book/10.1007/978-981-16-1438-5

"Kernel Methods for Machine Learning with Math and Python"

https://link.springer.com/book/10.1007/978-981-19-0401-1

# Discrete Mathematics

"CMU 21-228 Discrete Mathematics (prof. Poh-Shen Loh"

https://www.math.cmu.edu/~ploh/2021-228.shtml

# Mathematical Logic

"Mathematical Logic Through Python"

https://www.logicthrupython.org/

# CS Complexity and Theory:

Courses by Ryan O'Donnell at CMU

reducesuffering
https://fullstackopen.com/en/

Full Stack Open, a free course by University of Helsinki, is very good on quickly teaching the core concepts for modern frontend and backend in the JS ecosystem. Such a good primer on React and the rest of the things, CI/CD, DB, backend API, auth, etc. involved in fullstack development.

idrios
Here's a pretty good website that gives direction on the path to competence/mastery for various domains of software development.

https://roadmap.sh/