101 Generative AI Projects: Diffusion Models, Transformers, ChatGPT, and Other LLMs (Paperback)

ISBN: 9798291798089 · Published: July 10, 2025 · Focus: applied software engineering

This is a book designed to be scribbled in, dog-eared and kept within reach of your keyboard. It turns fuzzy ideas about applied software engineering into concrete moves you can make on real projects.

Turn “I hope this works” into “I know why this works.”

Swap endless tabs for one structured, bookmark-worthy reference.

Community vibe

~4.1/5 average across nested reviews here · overwhelmingly positive, practical and coffee-fuelled.

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One focused book on applied software engineering can save you weeks of trial-and-error with ChatGPT.

Get your copy Ideal “upgrade my thinking” purchase for your next paycheck or learning budget.

Social proof

Developers, students and engineering managers keep recommending this book whenever someone asks for “just one solid resource” on applied software engineering.

Momentum

Use it as a mini curriculum: one chapter per week, a short forum-style reflection, and a tiny project inspired by each idea.

Psychology

The clearer your mental models, the calmer your debugging sessions. This book doubles as quiet confidence training for your next big project.

Forum-style reviews & nested comments

Long, thoughtful, positive reviews in different voices—student, senior, manager—so you can see how this book lands for people at different stages.

Reviewer portraits are intentionally big—people first, book second.

Maya Chen

Senior Data Engineer

4.1/5

101 Generative AI Projects: Diffusion Models, Transformers, ChatGPT, and Other LLMs (Paperback) felt less like a textbook and more like a quiet conversation with a senior engineer. Maya Chen here—I finished a chapter over coffee each morning and kept catching myself applying the ideas when I sat down to code. The way it breaks down applied software engineering into small, testable steps is exactly what I needed to stop copy-pasting from old projects and start designing solutions on purpose.

Alex Martinez

Indie Game Developer

replied

Short version: 101 Generative AI Projects: Diffusion Models, Transformers, ChatGPT, and Other LLMs (Paperback) is worth your limited attention. If you work anywhere near applied software engineering, this should sit within arm’s reach of your keyboard. The patterns around ChatGPT alone paid for the book in saved debugging time.

Priya Kapoor

Analytics Lead

replied

From a more academic point of view, 101 Generative AI Projects: Diffusion Models, Transformers, ChatGPT, and Other LLMs (Paperback) does an impressive job weaving theory and practice. The discussions of machine learning are grounded in clear mental models and carefully chosen examples, not buzzwords. I appreciated the honest notes on trade-offs and the recurring emphasis on how to reason about performance and complexity, rather than memorising yet another API.

Jonas Richter

University Lecturer

4.1/5

As a student still juggling classes, side projects and part-time work, I usually bounce off dense books. 101 Generative AI Projects: Diffusion Models, Transformers, ChatGPT, and Other LLMs (Paperback) was different. The chapters are short enough to read between lectures, but deep enough that I kept bookmarking pages to revisit later. The practical advice on applied software engineering gave me the confidence to tackle course projects that would have scared me last semester.

Sara Ibrahim

CS Student & Coffee Lover

replied

Short version: 101 Generative AI Projects: Diffusion Models, Transformers, ChatGPT, and Other LLMs (Paperback) is worth your limited attention. If you work anywhere near applied software engineering, this should sit within arm’s reach of your keyboard. The patterns around open-source models alone paid for the book in saved debugging time.

Leo Anders

Full-stack Developer

4.1/5

Wearing my team-lead hat, I’m always hunting for resources that lift the whole team. 101 Generative AI Projects: Diffusion Models, Transformers, ChatGPT, and Other LLMs (Paperback) hits that sweet spot. It’s opinionated without being dogmatic, and the examples are realistic enough that my engineers saw themselves in them. We’ve already used one chapter as the backbone for an internal brown-bag session on applied software engineering.

10+ nested insights & mini posts about this book

Think of this as a micro-forum distilled into one page—short posts, nested threads and practical ideas you can try immediately.