The Computer Science Book: For Self-Taught Developers, 2nd Edition

Tom Johnson’s The Computer Science Book is a guided tour through the ideas that shape modern software — from computation theory and computer architecture to distributed systems, machine learning, and large language models. It was written for the self-taught developer who already writes code but wants to understand what’s happening under the hood.

A Practical Route Through Computer Science

This second edition brings together thirteen focused chapters that build on one another, offering a structured survey of the topics usually scattered across a full computer science degree. The emphasis stays on ideas that matter in daily programming work: how algorithms scale, how operating systems manage resources, how networks deliver data reliably, and how databases keep information consistent.

Thirteen Focused Chapters

• Theory and algorithms: computation, complexity, data structures, and abstract types.
• Systems: computer architecture, operating systems, networking, concurrency, and distributed systems.
• Languages and data: programming paradigms, compilation, relational algebra, SQL, and database architecture.
• Modern AI: machine learning, deep learning, generative models, and large language models.

Built for Self-Taught Developers

If you learned to code through bootcamps, online courses, or independent projects, this book fills the gaps that often remain. It does not assume you already have a formal CS background, and it avoids getting lost in notation or exhaustive textbook detail. Instead, each chapter focuses on the mental models that make the underlying systems easier to reason about.

Connections and Recurring Themes

Throughout the book, Johnson highlights three recurring ideas: the layers of abstraction that manage complexity, the fundamental limits and tradeoffs that shape what is possible, and the conventions and contracts that let separate systems work together. These themes connect topics as different as processor gates and distributed consensus, helping the reader see computing as a coherent whole.

A Launchpad for Deeper Study

Each chapter concludes with practical further reading suggestions, pointing readers toward influential textbooks and advanced topics that did not fit in the chapter. The result is not just a single reading experience but a durable reference for planning future learning. For developers who have felt the ground shifting beneath them as AI becomes central to software work, this updated edition offers a timely, readable foundation.