The Computer Science Book, Second Edition is a practical map of computer science for working developers. It gives you the foundations beneath the abstractions, without asking you to reconstruct a whole degree from scratch.
The online version previews the chapters below, including the three new V2 chapters on machine learning, deep learning, and large language models and AI.
Automata, computability, and algorithmic complexity
Arrays, linked lists, hash maps, sorting, and searching
Binary, logic gates, processors, and memory hierarchy
Processes, memory management, and file systems
TCP/IP, DNS, HTTP, and how the internet works
Threads, locks, and asynchronous programming
CAP theorem, consistency models, and consensus protocols
Paradigms, type systems, and language design
SQL, indexes, B-trees, and concurrency control
Parsing, ASTs, code generation, and optimization
Learning from data, uncertainty, evaluation, and where ML fits into real software systems
Neural networks, learned representations, and the architectures behind modern AI
Transformers, post-training, and the systems perspective behind LLM-powered software