This repository lists links to high-quality books and open Computer Science courses taught by world-class universities and talented individuals.
Pull requests and issues are welcome!
- UC Berkeley β CS162: Operating Systems and System Programming (Fall 2020)
- MIT β 6.S081: Operating Systems (Fall 2020)
- University of Virginia β CS4414: Operating Systems in Rust
- University of Massachusetts β CS377: Operating Systems
- Bilkent University β CS342: Operating Systems
- Philipp Oppermann β Writing an OS in Rust (Blog)
- CS Primer β Operating Systems
- You Are the OS (Game)
- University of WisconsinβMadison β Operating Systems: Three Easy Pieces (Book)
- Brown University β CS173: Programming Languages
- San Jose State University β CMPE152: Compiler Design (Winter 2021)
- Cornell University β CS6120: Advanced Compilers (Self-Guided)
- California State University β CSC151: Compiler Construction
- MIT β 6.035: Computer Language Engineering
- Arizona State University β CSE340: Principles of Programming Languages
- Immo Landwerth β Building a Compiler in C# (by Immo Landwerth, C# design team member at Microsoft)
- Catholic University of Louvain β LINGI2132: Languages and Translators
- Static Program Analyses
- Compiler Design (Playlist)
- LLVM + MLIR: How to Build a Compiler
- Stanford β Compilers
- Stanford Online β Compilers (edX)
- MIT β Structure and Interpretation of Computer Programs (Book, SICP)
- Writing an Interpreter in Go (Book)
- Writing a Compiler in Go (Book)
- Douglas Thain, University of Notre Dame - Intro to Compilers & Language Design (Book)
- Robert Nystrom β Crafting Interpreters (Book)
- Nora Sandler β Writing a C Compiler (Book)
- C++ Links β Compilers Resources
- NetworkChuck β Free CCNA 200-301 + You Suck at Subnetting
- Jim Kurose β Computer Networking: A Top-Down Approach (8th Ed.)
- Ben Eater β Networking Tutorials
- Game Networking Resources
- Eli the Computer Guy β Networking
- Beejβs Guide to Network Programming
- Stanford β CS231n: Convolutional Neural Networks
- Stanford β CS231n (with Andrej Karpathy)
- Andrej Karpathy β Neural Networks: Zero to Hero
- Stanford β CS229: Machine Learning (with Andrew Ng)
- Carnegie Mellon University β Deep Learning
- UC Berkeley β CS188: Introduction to AI
- Cornell β CS4780: Machine Learning for Decision Making
- MIT β 6.S191: Introduction to Deep Learning (Updated Yearly)
- MIT β 6.S094: Machine Learning (with Lex Fridman)
- The Coding Train β Neural Networks
- Weights & Biases β Math for Machine Learning
- Duke University β Data Science Math Skills (Coursera)
- DeepLearning.AI + Stanford β ML Specialization (Coursera)
- Data Science in Python (DataQuest)
- ETH ZΓΌrich β Mathematics of Machine Learning (Spring 2021)
- Imperial College London β Mathematics for ML: Linear Algebra
- Imperial College London β Mathematics for ML: Multivariate Calculus
- Ian Goodfellow, Yoshua Bengio, Aaron Courville β Deep Learning (Book)
- Stanford β Mathematics for Machine Learning (Book)
- Ronald Kneusel β Math for Deep Learning (Book)
- Carnegie Mellon University β Intro to Database Systems (Fall 2024)
- Carnegie Mellon University β Advanced Database Systems (Spring 2024)
- Carnegie Mellon University β 15-799: Query optimization (Spring 2025)
- UC Berkeley β CS186: Introduction to Database Systems
- MIT β 6.824: Distributed Systems
- Martin Kleppmann β Distributed Systems Lecture Series (Designing Data-Intensive Applications)
- UC Berkeley β CS61C: Great Ideas in Computer Architecture
- Carnegie Mellon University β 15-213: Introduction to Computer Systems
- Carnegie Mellon University β Computer Architecture (Playlist)
- Ron White β How Computers Really Work (Book)
- Bryant & OβHallaron β Computer Systems: A Programmerβs Perspective (CS:APP Book)
- Neal Ford β Fundamentals of Software Architecture (Book)
- Neal Ford β Software Architecture: The Hard Parts (Book)
- Sam Newman β Building Microservices (Book)
- Martin Kleppmann β Designing Data-Intensive Applications (Book)
- MIT β 18.06SC: Linear Algebra
- MIT β 18.06 Linear Algebra with Gilbert Strang
- 3Blue1Brown β Essence of Linear Algebra
- DeepLearning.AI β Machine Learning: Linear Algebra (Coursera)
- MIT β Mathematics for Computer Science
- TODO
- TODO
- Harvard β Statistics 110: Probability (Joe Blitzstein)
- Will Kurt β Statistics the Fun Way (Book)
- Alex Reinhart β Statistics Done Wrong (Book)
- MIT β Introduction to Algorithms
- UC Berkeley β CS61B: Data Structures
- Harvard β COMPSCI 224: Advanced Algorithms
- Algorithms: Jeff Erickson (Free Book)
- MIT β 6.858: Computer Systems Security (Spring 2020)
- Stanford β CS253: Web Security
- Arizona State University β CSE545: Software Security
- pwn.college β Free Security Training
- Sam Grubb β How Cybersecurity Really Works (Book)
- Malcolm McDonald β Web Security for Developers (Book)
- GOsling β A Tour of Go Resources
- Golang Internals Resources
- Dmitry Vyukov β Go Internals (Book, Partial)
- StackOverflow β How to Learn Go Internals
- Matt Holiday β Go Class (YouTube)