[books]

Recommended Books

These are books I’ve personally found useful over the years — for algorithms, web development, JavaScript, modern data/AI thinking, and even the science of how people actually learn. If you’re serious about this line of work, any one of these would make a good long-term reference.

Cover of Introduction to Algorithms Introduction to Algorithms
Thomas H. Cormen, Charles E. Leiserson, Ronald L. Rivest, Clifford Stein
MIT Press; Hardcover – 1st edition
Approx. 1000+ pages
ISBN: 0262031418

This is the classic algorithms text. It’s not light reading, but it gives you the mathematical and conceptual foundation for data structures, sorting, graph algorithms, and more. I keep it here partly for historical reasons and partly because the way of thinking it teaches still holds up.

Cover of The Algorithm Design Manual The Algorithm Design Manual (2nd Edition)
Steven S. Skiena
Springer; 2010; Hardcover, 730 pages
ISBN-13: 9781849967204

Where Cormen is formal, Skiena is practical. This book is full of real-world stories and a “hitchhiker’s guide” of algorithmic problems. If you want to get better at choosing the right tool for the job instead of just memorizing code, this is a very readable companion to the heavier texts.

Cover of HTML and CSS: Design and Build Websites HTML & CSS: Design and Build Websites
Jon Duckett
Wiley; 2011; Full-color paperback, ~500+ pages
ISBN-13: 9781118008188

This is still one of the clearest visual introductions to HTML and CSS. Large diagrams, color-coded examples, and short explanations make it ideal for students and for anyone who wants to “see” how markup and styling fit together without drowning in jargon.

Cover of CSS: The Definitive Guide (4th Edition) CSS: The Definitive Guide, 4th Edition
Eric A. Meyer, Estelle Weyl
O’Reilly Media; 2017; Paperback, 1090 pages
ISBN-13: 9781449393199

When you’re ready to go beyond “it works” and into “why it works”, this is the reference. Layout, selectors, specificity, responsive techniques — it’s all here, and it’s where you go when a browser does something odd and you actually want to understand why.

Cover of JavaScript: The Definitive Guide (7th Edition) JavaScript: The Definitive Guide, 7th Edition
David Flanagan
O’Reilly Media; 2020; Paperback, 700+ pages
ISBN-13: 9781491952023

This is the modern “big JS book” — covering the language itself, the browser environment, and newer features like promises, async/await, and modules. Not a quick tutorial, but an excellent long-term reference for serious front-end and full-stack work.

Cover of JavaScript and jQuery: Interactive Front-End Web Development JavaScript & jQuery: Interactive Front-End Web Development
Jon Duckett
Wiley; 2014; Full-color paperback, ~640 pages
ISBN-13: 9781118531648

This pairs nicely with Duckett’s HTML/CSS book. It’s highly visual and shows how JavaScript manipulates the DOM, with jQuery used as training wheels for thinking in terms of events, animations, and interactive components. Great for visual learners and people just getting into front-end behavior.

Cover of Designing Data-Intensive Applications Designing Data-Intensive Applications
Martin Kleppmann
O’Reilly Media; 2017; Paperback, 616 pages
ISBN-13: 978-1449373320

If you want to think beyond single scripts and into robust systems — storage, caching, consistency, distributed data, and scalability — this book is the modern classic. It’s especially useful if you ever find yourself designing APIs or back-end architectures for real users.

Cover of Prediction Machines: The Simple Economics of Artificial Intelligence Prediction Machines, Updated and Expanded: The Simple Economics of Artificial Intelligence
Ajay Agrawal, Joshua Gans, Avi Goldfarb
Harvard Business Review Press; 2022; Hardcover, 304 pages
ISBN-13: 9781647824679

This is a non-technical but very clear explanation of what AI really changes: it makes prediction cheap. That framing helps executives, developers, and educators think about where AI fits into decision-making, workflows, and new products — including things like Ask Tedd / Ask Sage.

Cover of Make It Stick: The Science of Successful Learning Make It Stick: The Science of Successful Learning
Peter C. Brown, Henry L. Roediger III, Mark A. McDaniel
Harvard University Press; 2014; Hardcover, 336 pages
ISBN-13: 9780674729018

If you teach, mentor, or just want to learn more efficiently yourself, this one is worth reading. It summarizes decades of cognitive science on how people actually remember things — retrieval practice, spacing, interleaving — and turns it into practical habits for both students and instructors.