Computer Science From Scratch

You know how to write Python. Now master the computer science that makes it work. If you've been programming for a while, you may have found yourself wondering about the deeper principles behind the code. How are programming languages implemented? What does an interpreter really do? How does the microprocessor execute instructions at a fundamental level? How does a machine learning algorithm make decisions? Computer Science from Scratch is for experienced Python programmers who want to fill in those gaps-not through abstract lectures, but through carefully designed projects that bring core CS concepts to life. Understanding these fundamental building blocks will make you a more versatile and effective programmer. Each chapter presents a focused, hands-on project that teaches a fundamental idea in computer science: - INTERPRETERS: Understand syntax, parsing, and evaluation by writing a BASIC interpreter- EMULATORS: Learn computer architecture by building an NES emulator from the ground up- GRAPHICS: Explore image manipulation and algorithmic art through computer graphics projects- MACHINE LEARNING: Demystify classification by implementing a simple, readable KNN model These projects aren't about building tools-they're structured lessons that use code to reveal how computing works. Each chapter concludes with real-world context, thoughtful extensions, and exercises to deepen your understanding. Authored by David Kopec, a computer science professor and author of the popular Classic Computer Science Problems series, this is not a beginner's book, and it's not a theory-heavy academic text. It's a practical, code-driven introduction to the essential ideas and mechanisms of computer science-written for programmers who want more than syntax. If you've been writing Python and are ready to explore the foundations behind computing, this book will guide you there-with clarity, depth, and purpose.

David Kopec is an associate professor of computer science at Albright College. He is the author of five programming books, including the Classic Computer Science Problems series, and spent several years as an iOS developer for startups. In addition to his teaching work, David is an avid podcaster and indie app developer with an MS in computer science from Dartmouth and an EMBA from Quantic.

Introduction Part I: Interpreters Chapter 1: The Smallest Possible Programming Language Chapter 2: Writing a BASIC Interpreter Part II: Computational Art Chapter 3: Retro Image Processing Chapter 4: A Stochastic Painting Algorithm Part III: Emulators Chapter 5: Building a CHIP-8 Virtual Machine Chapter 6: Emulating the NES Game Console Part IV: Super Simple Machine Learning Chapter 7: Classification with K-Nearest Neighbors Chapter 8: Regression with K-Nearest Neighbors Afterword Appendix: Bitwise Operations