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  1. OpenIntro Statistics
    Includes 1st, 2nd, 3rd, and 4th Editions
    OpenIntro, Christopher Barr, Mine Cetinkaya-Rundel, and David Diez

    A complete foundation for Statistics, also serving as a foundation for Data Science. Leanpub revenue supports OpenIntro (US-based nonprofit) so we can provide free desk copies to teachers interested in using OpenIntro Statistics in the classroom and expand the project to support free textbooks in other subjects. More resources: openintro.org.

  2. Product Engineering with AI
    A practical guide to product engineering in an AI native era
    Addy Osmani and Hassan Djirdeh

    A practical guide to product engineering in an AI native era, where building shifts from manual construction to steering tools, editors, and agents. Product Engineering with AI covers platforms, agentic workflows, prompting, code quality, UX, and responsible practices for getting from prototype to production. 

  3. Residuality Theory is a new way to think about the design of software systems that explains why we experience design the way we do, why certain things seem to work only sporadically, and why certain architects get it right so often regardless of which tools they use. A new, scientific approach is defined that fuses Software Engineering, Complexity Science, and Philosophy to produce an entirely new way to think about how to design software. The result is a theoretical base that allows architecture to finally become its own discipline.

  4. The practical guide to AI-first teamwork. Includes access to the 'CollabAI AI companion' that helps you run your first session immediately. Most teams have fast individuals—but a slow system. AI can change that. CollabAI is the manual for teams who want to stop waiting and start flowing. It moves beyond "chatting with a bot" to a new collaborative rhythm where humans and AI build, test, and decide together in real time. Inside, you’ll discover:The Framework: How to run CollabAI sessions that compress weeks of work into hours.The Science: Why "System 2 Rituals" and psychological safety are the hard requirements for speed.The Scale: How to apply Joe Justice’s principles (Justice Boards & DSM) to run entire organizations without managers.The Future: How to transition safely to Agentic AI workflows using the Agion Pattern.Start optimizing the flow.

  5. Generative AI for Science
    A Hands-On Guide for Students and Researchers
    J. Paul Liu

    Bridge AI and science with this hands-on guide. Whether you're a researcher learning ML or an engineer entering scientific applications, build real systems across chemistry, biology, physics & climate. Master Transformers, Diffusion Models & GNNs for scientific discovery. 500+ pages, 50+ Colab notebooks. Design molecules, predict proteins, accelerate climate models—all hands-on, zero setup required.

  6. The SysML v2 Book
    Practical Insights and Comprehensive Reference
    Tim Weilkiens and Vince Molnár

    Learn SysML v2 with the ultimate guide for all skill levels in MBSE. Authored by insiders, it's your key to unlocking the full potential of system modeling and a passport to mastering your MBSE.

  7. A clear, illustrated guide to large language models, covering key concepts and practical applications. Ideal for projects, interviews, or personal learning.

  8. CISSP: The Last Mile
    Your guide to the finish line
    Pete Zerger

    The book covers every topic in the latest CISSP exam syllabus, organized in a format that makes it easy to drill down on specific exam domains and concepts at-a-glance, making it an essential exam resource for anyone who aims to prepare for the exam without wasting time or money.

  9. Logic is the most important branch of math to software engineering. Knowing logic opens up a vast world of development techniques, from everyday tricks of the trade to exotic tools for cracking impossible tasks. This book teaches the basics of logic and nine special logic-powered techniques: property testing, decision tables, constraint solving, and more. Over 40 exercises are provided to help readers master the material. No prior math background required!

  10. How to Build and Fine-Tune a Small Language Model
    A Step-by-Step Guide for Beginners, Researchers, and Non-Programmers
    J. Paul Liu

    You don’t need massive compute or big-tech resources to build real AI. This hands-on guide shows you how to build and fine-tune your own small language model—from scratch—using accessible tools like Google Colab. Learn transformers step-by-step, train and align models on your own data, and deploy practical AI systems that run on consumer GPUs. If you’ve ever wondered “Can I build my own model?”—this book proves the answer is yes.

  11. Discover how to elevate your QA skills to the cloud.Testing in the Sky takes you through the tools, strategies, and mindset needed to ensure quality in modern, scalable cloud systems. Perfect for testers aiming to stay ahead in a fast-changing tech landscape.

  12. Transform the way you test in Agile.Effective Testing in Agile/Scrum reveals how smart QA strategies can drive faster, better software delivery. Learn how to embed testing into every sprint, boost collaboration, and ensure quality without slowing down the team. Perfect for Agile teams aiming to build with confidence.

  13. Introduction to Modern Statistics
    OpenIntro, Mine Cetinkaya-Rundel, and Johanna Hardin

    The book is also available in paperback for $25. Paperback royalties go to OpenIntro (US-based nonprofit), and the optional Leanpub PDF contributions go to authors to fund their time on this book.

  14. The Hundred-Page Language Models Book
    hands-on with PyTorch
    Andriy Burkov

    Master language models through mathematics, illustrations, and code―and build your own from scratch!

  15. Introduction to GIS Programming
    A Practical Python Guide to Open Source Geospatial Tools
    Qiusheng Wu

    Unlock the power of geospatial data with Python! This hands-on guide is designed for beginners and intermediate users eager to explore spatial analysis and interactive mapping using open-source tools. You'll learn how to work with real-world data through practical examples and build skills in Python programming, vector and raster analysis, web mapping, and cloud computing. Whether you're a student, researcher, GIS professional, or data scientist, this book will equip you with the tools to tackle geospatial challenges with confidence. Color-print copies are available through Amazon.