The Computer Science Book

Sat, 20 Jun 2026 10:00:00 +0100

These articles are a collection of knowledge gems I’ve gathered over time on a range of computer science topics.

The Computer Science Book

Sun, 18 Jul 2021 15:59:52 +0100

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.

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Preview chapters

Theory of computation Preview
Automata, computability, and algorithmic complexity
Algorithms and data structures Preview
Arrays, linked lists, hash maps, sorting, and searching
Computer architecture Preview
Binary, logic gates, processors, and memory hierarchy
Operating systems Preview
Processes, memory management, and file systems
Networking Preview
TCP/IP, DNS, HTTP, and how the internet works
Concurrent programming Preview
Threads, locks, and asynchronous programming
Distributed systems Preview
CAP theorem, consistency models, and consensus protocols
Programming languages Preview
Paradigms, type systems, and language design
Databases Preview
SQL, indexes, B-trees, and concurrency control
Compilers Preview
Parsing, ASTs, code generation, and optimization
Machine learning Preview
Learning from data, uncertainty, evaluation, and where ML fits into real software systems
Deep learning Preview
Neural networks, learned representations, and the architectures behind modern AI
Large language models and AI Preview
Transformers, post-training, and the systems perspective behind LLM-powered software

The Computer Science Roadmap

Mon, 01 Jan 0001 00:00:00 +0000

Most self-taught developers pick up computer science in a random order — a bit from a video here, a blog post there — and end up with gaps they can’t even see.

This free, 45-page roadmap lays out the whole territory: the core areas of computer science, the order that actually makes them click, and the parts you can safely skip when you’re learning on your own.

What’s inside

What to learn — the major areas of computer science and how they fit together.
In what order — a carefully planned sequence from fundamentals up to systems, tailored to your situation.
What to skip — the topics that aren’t worth your time right now.

Who it’s for

The roadmap charts a separate path for four kinds of learner:

Working developers — you can ship, but you can feel the sand under your feet. You want to know what you’ve been missing, and how far to trust your AI tools.
Just starting out or switching careers — you can code a little, but how it all fits together is still a mystery. You want a way in that doesn’t assume you already know the jargon.
Interview preppers — you need real mental models of algorithms, data structures, and system design, not rote answers that fall apart under questioning.
Future CS students — you’re weighing up whether to study computer science, and you want an honest overview before committing years to it.