🐯 Princeton CS unofficial reading list (Spring 2025)
←Fall 2024 | Fall 2025→
This is an unofficial list of books that are recommended in Spring 2025 computer science classes at Princeton
The books marked with a ✨ are ones I’ve been interested enough in to read at length
| Freshman level | |
|---|---|
| Computer Science: An Interdisciplinary Approach COS 126 |
• Computer Science: An Interdisciplinary Approach by Sedgewick & Wayne |
| Sophomore level | |
|---|---|
| Intro. to Programming Systems COS 217 |
• C Programming: A Modern Approach by K.N. King • ARM 64-Bit Assembly Language by Pyeatt & Ughetta • ✨ The Practice of Programming✨ by Kernighan & Pike • Linux Pocket Guide: Essential Commands by Daniel J. Barrett |
| Algorithms & Data Structures COS 226 |
• ✨Algorithms✨ by Sedgewick & Wayne |
| Reasoning About Computation COS 240 |
• Mathematics for Computer Science by Lehman, Leighton & Meyer |
| Junior level | |
|---|---|
| Intro. to Machine Learning COS 324 |
• Introduction to Machine Learning by Arora, Park, Jacob & Chen • An Introduction to Statistical Learning by James, Witten, Hastie & Tibshirani • Speech & Language Processing by Jurafsky & Martin • Reinforcement Learning: An Introduction by Sutton & Barto • ✨ Mathematics for Machine Learning ✨ by Deisenroth, Faisal & Ong • Deep Learning by Goodfellow, Bengio & Courville • Introduction to Probability by Blitzstein & Hwang • Learning Data Science: Data Wrangling, Exploration, Visualization & Modeling with Python by Lau, Gonzalez & Nolan • Pattern Recognition & Machine Learning by Christopher M. Bishop • Introduction to Machine Learning by Etienne Bernard |
| Advanced Programming Techniques COS 333 |
• ✨ The Practice of Programming ✨ by Kernighan & Pike • Python in a Nutshell: A Desktop Quick Reference by Martelli, Ravenscroft, Hoden & McGuire • Flask Web Development: Developing Web Applications with Python by Miguel Grinberg • JavaScript: The Definitive Guide: Master the World’s Most-Used Programming Language by David Flanagan • Beginning Software Engineering by Rod Stephens |
| Senior level | |
|---|---|
| Intro. to Machine Translation COS 401 / LIN 304 / TRA 301 |
• Readings in Machine Translation by Nirenburg, Somers & Wilks • Neural Machine Translation by Philipp Koehn • Speech & Language Processing by Jurafsky & Martin |
| Operating Systems COS 417 |
• Operating Systems: Three Easy Pieces by Arpaci-Dusseau & Arpaci-Dusseau |
| Distributed Systems COS 418 |
• The Go Programming Language by Donovan & Kernighan • Distributed Systems: Principles & Paradigms by Tanenbaum & van Steen • Guide to Reliable Distributed Systems: Building High-Assurance Applications & Cloud-Hosted Services by Kenneth P. Birman |
| Information Security COS / ECE 432 |
• Security Engineering: A Guide to Building Dependable Distributed Systems by Ross Anderson • Computer Security by Dieter Gollmann • The Codebreakers: The Comprehensive History of Secret Communication from Ancient Times to the Internet by David Kahn •✨Practical Cryptography✨ by Ferguson & Schneier • Building Secure Software: How to Avoid Security Problems the Right Way by Viega & McGraw • The Tangled Web: A Guide to Securing Modern Web Applications by Michal Zalewski |
| Intro. to Reinforcement Learning COS 435 / ECE 433 |
• Grokking Deep Reinforcement Learning by Miguel Morales • An Introduction to Deep Reinforcement Learning by Francois-Lavet, Henderson, Islam, Bellemare & Pineau • Reinforcement Learning: An Introduction by Sutton & Barto • Reinforcement Learning: Theory& Algorithms by Agarwal, Jiang, Kakade & Sun |
| Economics & Computation COS 445 |
• Game Theory, Alive by Karlin & Peres • Networks, Crowds & Markets: Reasoning about a Highly Connected World by Easley & Kleinberg • Algorithmic Game Theory by Nisam, Roughgarden, Tardos & Vazirani • Handbook of Computational Social Choice by Brandt, Conitzer, Endriss, Lang & Procaccia |
| Innovating Across Technology, Business & Marketplaces COS / EGR 448 |
• ✨The Everything Store: Jeff Bezos & the Age of Amazon✨ by Brad Stone • In the Plex: How Google Thinks, Works & Shapes Our Lives by Steven Levy • ✨The Hard Thing About Hard Things: Building a Business When There Are No Easy Answers✨ by Ben Horowitz • Venture Deals: Be Smarter Than Your Lawyer & Venture Capitalist by Feld & Mendelson • The Airbnb Story: How Three Ordinary Guys Disrupted an Industry, Made Billions & Created Plenty of Controversy by Leigh Gallagher • The Innovator’s Dilemma: When New Technologies Cause Great Firms to Fail by Clayton M. Christensen • Crush It!: Why Now Is The Time To Cash In On Your Passion by Gary Vaynerchuk • Art of the Start 2.0: The Time-Tested, Battle-Hardened Guide for Anyone Starting Anything by Guy Kawasaki • Demand: Creating What People Love Before They Know They Want It by Slywotzky & Weber • Rework by Fried & Heinemeier Hansson • Positioning: The Battle for Your Mind by Ries & Trout • The Lean Startup: How Today’s Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses by Eric Ries • Running Lean: Iterate From Plan A to a Plan That Works by Ash Maurya • The Startup Owner’s Manual: The Step-by-Step Guide for Building a Great Company by Blank & Dorf • Business Model Generation: A Handbook for Visionaries, Game Changers & Challengers by Osterwalder & Pigneur • Delivering Happiness: A Path to Profits, Passion & Purpose by Tony Hsieh • Powerful: Building a Culture of Freedom & Responsibility by Patty McCord •✨Crossing the Chasm: Marketing & Selling Disruptive Products to Mainstream Customers✨ by Geoffrey A. Moore •✨Good to Great: Why Some Companies Make the Leap & Others Don’t✨ by Jim Collins |
| Computer Architecture COS / ECE 475 |
• Computer Architecture: A Quantitative Approach by Hennessy & Patterson |
| Natural Language Processing COS 484 |
• Speech & Language Processing by Jurafsky & Martin • Introduction to Natural Language Processing by Jacob Eisenstein • Foundations of Statistical Natural Language Processing by Manning & Schutze |
| Neural Networks: Theory & Applications COS 485 |
• Dive Into Deep Learning by Zhang, Lipton, Li & Smola • Deep Learning for Coders with Fastai & PyTorch: AI Applications Without a PhD by Howard & Gugger |
| Graduate level | |
|---|---|
| Advanced Computer Systems COS 518 |
See website for paper list |
| Great Moments in Computing COS / ECE 583 |
See website for paper list |
| AI Safety & Alignment COS 598A |
See website for paper list |
| Machine Behavior COS 598B |
See website for paper list |
| Cryptographic Proof Systems COS 598D |
• Foundations of Cryptography by Oded Goldreich See website for paper list |