The Computer Science Book: For self-taught developers Kindle Edition

You learned to code. But can you explain how it actually works?A senior engineer mentions cache invalidation, transaction isolation, or the CAP theorem. You nod along, then quietly Google it afterwards. You can build things, but underneath there are gaps you feel every day.The Computer Science Book helps you close them.Across thirteen chapters, it gives self-taught developers a practical introduction to the core areas of computer science. Instead of dumping facts, it builds intuition with concrete examples and clear explanations. Each chapter distils what matters from subjects that normally fill entire textbooks.What readers say:"An essential read for anyone who felt they missed out on a computer science education. Tom distils each topic beautifully and succinctly. It was a joy to read." — Adrian Booth, senior engineer"Incredibly helpful for rebuilding the missing foundations behind highly abstracted systems. The networking chapter immediately changed how I think about requests, responses, and system boundaries." — Kelven Opoku, backend engineer"This book covers all the topics I lacked confidence in. I’ve been able to apply the content to my day-to-day work. I really recommend this book." — John Whiles, staff engineerThis fully revised and expanded second edition includes three new chapters on machine learning, deep learning, and large language models & AI, along with substantial updates across the original material.Thirteen chapters covering:Theory of computation — what computers can and can't doAlgorithms and data structures — choosing the right tool for the jobComputer architecture — what happens when your code actually runsOperating systems — processes, memory, and the software managing it allNetworking — from electrical signals to HTTPConcurrent programming — threads, locks, and what breaks in parallelDistributed systems — what changes across multiple machinesProgramming languages — how language design shapes the way you thinkDatabases — transactions, indexing, and query planningCompilers — how source code becomes something a machine can executeNEW: Machine learning — from linear regression to random forestsNEW: Deep learning — neural networks, CNNs, and generative AINEW: Large language models & AI — how ChatGPT works and what's coming at the frontierPerfect for self-taught developers, bootcamp graduates, working engineers, career changers, and anyone preparing for technical interviews. No CS degree required — just the ability to read code. Each chapter stands alone and includes curated further reading for going deeper. Read more