The curriculum library

The titles below come with grading, practice, hints, and mastery tracking. Open books are free forever, and licensed titles are priced per student. A few are marked as coming soon. Don’t see yours? Bring it.

Popular CS textbooks, with grading and practice built in

Mix and match curricula for your class, or add your own

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Generative AI: Programming with LLMs
2Sigma School
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LOGIC GYM Java Beginner 01 / 05 Only on Alps
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Nifty Assignments — Java edition
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AP Cybersecurity
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AP Cybersecurity Practice Problems
Java Methods: Object-Oriented Programming and Data Structures
Barbara Ericson, Beryl Hoffman
Python Data Science Handbook
Inferential Thinking
Ani Adhikari, John DeNero, David Wagner
Beryl Hoffman, Jennifer Rosato
Python for Everybody
Dr. Charles Severance, Barbara Ericson
Coding in Python
Algorithms & Data Structures Using Python
How To Think Like A Computer Scientist: C++ Version
How To Think Like A Computer Scientist: Python Version
Bradley N. Miller, David Ranum, Barbara Ericson, Mark Guzdial
Java, Java, Java
R. Morelli, R. Walde
Java for Python Programmers
Jan Pearce
Learning Data Science
Think Python
Think Stats
Think Bayes
AP Computer Science Principles: Practice & Exams
Java Short Labs
Python Labs
Parth Sarin, Michael Cooper, Sam Redmond
Coming Soon!
The Beauty and Joy of Computing
UC Berkeley, Education Development Center
Algorithms and Data Structures using Java
Bradley Miller, David Ranum, Roman Yasinovskyy, David Eisenberg
Fundamentals of Web Programming
Bradley N. Miller
Algorithms & Data Structures using C++
Brad Miller, David Ranum, Jan Pearce
C++ for Python Programmers
Jan Pearce, Bradley N. Miller
Foundations of Python Programming
Paul Resnick, Bradley N. Miller
Data Structures and Information Retrieval in Python
Allen B. Downey
Machine Learning From Scratch
Danny Friedman
Machine Learning for Beginners
Jen Looper, Stephen Howell, Francesca Lazzeri, Tomomi Imura, Cassie Breviu, Dmitry Soshnikov, Chris Noring, Anirban Mukherjee, Ornella Altunyan, Ruth Yakubu, Amy Boyd
Introduction to Cultural Analytics & Python
Melanie Walsh
How to Think Like a Data Scientist
Jan Pearce, Bradley N. Miller, et. al.
Data Science for Beginners
Jasmine Greenaway, Dmitry Soshnikov, Nitya Narasimhan, Jalen McGee, Jen Looper, Maud Levy, Tiffany Souterre, Christopher Harrison
Coming Soon!
Discrete Mathematics: An Open Introduction
Oscar Levin
Coming Soon!
CS50: AP Computer Science Principles
Harvard University

Don’t see the one you teach?

That’s common. Most departments teach from a publisher title, a colleague’s book, or course notes kept in Word or LaTeX. Bring yours and we’ll get it running.

It’s a published textbook

We work with publishers to bring titles to Alps, licensed per student. Tell us which one, and we’ll look into it.

It’s your own material

Our team imports it as a textbook. Your exercises become interactive activities, and your readings stay as they are. See how imports work.

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Start free with any open textbook

Pick a title, create a section, and have students working this week. No credit card or call needed.