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

173 points by ggr2342 a year ago

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.

blintz a year ago

The Stanford cryptography class ( and associated book ( 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; alternatively, there's a security class ( 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 a year ago . 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.

  • xwowsersx a year ago

    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 a year ago

      Doh, it says right there: "using either the suggested textbook or video lecture series, but ideally both" :)

  • hirvi74 a year ago

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

    Still faster than my CS degree.

sn9 a year ago

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.

ipnon a year ago

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.

jamestimmins a year ago

From Nand to Tetris: Build a Modern Computer from First Principles

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 a year ago

    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 a year ago

      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 only recommend the first one, so it depends what you want to get out of it and whether the approach resonates.

      • vmilner a year ago

        There are two editions of the book, but I believe each book covers the whole course.

newsoul a year ago

Surprised to see these introductory courses haven't been mentioned yet.

These courses [0] [1] are on EdX and are taught by UBC Professor Gregor Kiczales. The explanations are so lucid it made recursion click for me. You can audit these courses without paying a single dime. They are based on the book How to Design Programs [2] which has much more stuff than the courses.This book is used in UBC, UWaterloo, NorthEastern and many other places.

Along the same lines there is another book for beginners called A Data-Centric Introduction to Computing [3]. It is used in Brown for their introductory courses.





mattnewport a year ago

Some Coursera courses I have found to be good:

- Stanford algorithms specialization:

- University of Melbourne Discrete Optimization:

- Basic Modeling for Discrete Optimization:

- Advanced Modeling for Discrete Optimization:

Crafting Interpreters book mentioned elsewhere also very good.

  • Al0neStar a year ago

    "The Algorithm Specialization" that Tim Roughgarden teaches on Coursera/EdX is based on his book series "Algorithms Illuminated" and the lectures, slides and projects are up on the website so you dont need to take it on coursera/edx(UX hell, constant promo emails, time constraint).

subtract-smiles a year ago

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.

dondraper36 a year ago

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

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

reducesuffering a year ago

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.

marginalia_nu a year ago

If you ever decide to build a search engine, these are good resources.

Search Engines Information Retrieval in Practice

Croft, Metzler & Strohman (2015)


Introduction to Information Retrieval

Manning, Raghavan & Schütze (2008)


The Anatomy of a Large-Scale Hypertextual Web Search Engine

Page & Brin (2000)


Information Retreival

Rijsbergen (1979)

nyrikki a year ago

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"

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.

idrios a year ago

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

aviCC a year ago

Provides practical challenges with guidance for graduates in various subjects including Linux, Network, Security, and more..

Computer Science can sometimes be theoretical and learning from practical example is a must.

sarupbanskota a year ago

On (YC S22), you can learn to build your own Git, Docker, Redis etc — in any programming language.

It’s a great way to grok a variety of system design principles while getting to master a language of your choice

Al0neStar a year ago

# Programming

"A Data-Centric Introduction to Computing"

# Programming Language Theory

"Programming Languages: Application and Interpretation"

"Crafting Interpreters"

# Algorithms/Data Structures

* Pure C *

"Algorithmic Thinking: A Problem-Based Introduction"

# Competitive Programming/Interviews

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

"Elements of Programming Interviews in Python"

# Compilation

"Essentials of Compilation: An Incremental Approach in Python"

# Database Systems

"CMU: Intro to Database Systems"

"CMU: Advanced Database Systems"

# Calculus I/II & Real Analysis

"A Course in Calculus and Real Analysis"

"A Course in Multivariable Calculus and Analysis"

# Physics

"Matter and Interactions"

# 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"

"Sparse Estimation with Math and Python"

"Kernel Methods for Machine Learning with Math and Python"

# Discrete Mathematics

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

# Mathematical Logic

"Mathematical Logic Through Python"

# CS Complexity and Theory:

Courses by Ryan O'Donnell at CMU

# Cryptography

"Serious Cryptography: A Practical Introduction to Modern Encryption"

# Problem Solving

"Math 235: Mathematical Problem Solving"

# Computer Graphics

* Also look up the course by @pikuma for a pure c impl without OpenGL *

"Computer Graphics from Scratch: A Programmer's Introduction to 3D Rendering"

"The Ray Tracer Challenge A Test-Driven Guide to Your First 3D Renderer"

# Reverse Engineering

"Reverse Engineering for Beginners"


"SAT/SMT by Example"

Also Hakan Kjellerstrand's z3 page:

# Game Engine Development

* 2/4 volumes out (no digital format for the 2 pending volumes due to the authors "piracy" concerns *

"Foundations of Game Engine Development"

# Creative Coding

"Generative Design: Visualize, Program, and Create with JavaScript in p5.js"

Articles by Tyler Hobbs specially the one on "Flow Fields" :

Articles by Sighack specially the one on "Watercolor Techniques":

wwarner a year ago

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

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