The Story Behind AI Unmasked
Why I built AI Unmasked, and what I hope it gives you.
I am a computer scientist with a PhD, over 28 years of experience spanning software engineering and industrial R&D, and a deep belief that the hardest ideas become the clearest when someone who struggled to learn them takes the time to teach them well.
I started my career as a software engineer, but early on I discovered what was missing: research. The idea of working on a problem that does not have a solution yet, of continuously improving, seeking innovation, addressing limits and bottlenecks. That became my passion.
When I joined academia to pursue a master’s and then a PhD in computer science, it felt like an exchange. I brought my industry-driven sense of urgency and a strong orientation toward practical solutions. In return, I gained formalization, scientific rigor, and a depth of understanding that changed how I approach every problem.
It was not a walk in the park. I struggled with many advanced topics like complexity theory and formal methods, the kind of material that makes you question whether you belong. But I pushed through. And after going through fire to learn these things, I started helping classmates who were struggling with the same material.
The feedback I received surprised me: they found it easy to learn from me what they could not learn in class. That experience planted an idea that never left: I teach best the things I struggled the most to learn. And when I teach, I do it in the way I wish someone had taught me the first time.
When I was younger, I avoided math as much as I could. It felt abstract, disconnected, and punishing. That changed in graduate school, thanks to extraordinary advisors and professors who were truly passionate about teaching and science.
They showed me that math is both a language and a tool, and that changed my perspective entirely. Applied math is a powerful thing. Once you see a real problem being solved by math alone, once you see it in action, something clicks. You stop fearing it and start appreciating it.
That is exactly how math appears in AI Unmasked. Not as a wall to climb, but as a lens that makes everything sharper.
AI is everywhere now, but most of what people encounter is either oversimplified to the point of being misleading, or so technical that it excludes anyone without a graduate degree. Neither serves you.
I built AI Unmasked because I believe there is a middle path: technically honest, visually rich, hands-on, and accessible to anyone willing to pay attention. Every module reflects how I wish someone had introduced these ideas to me: with patience, with rigor, and without talking down.
AI Unmasked is not a single course. It is a growing series of courses, interactive labs, and Field Notes, a living library that evolves alongside the technology itself. It is a distillation of what I have built, researched, struggled with, and eventually understood, shared as part of my own ongoing, continued learning journey with AI.
Every concept is built from first principles with visual explanations. You will understand the why, not just the what.
A structured framework to evaluate any AI claim, product, or headline. You will know what is real and what is marketing.
Interactive simulations, live models, and exercises in every module. You build, test, and break things in your browser.
Every equation is also a picture. Gradient descent is walking downhill. Backpropagation is assigning blame. You will see it, not just read it.
Written by someone who builds with AI daily. Not a textbook repackaged, but insights from years of applied research and engineering.
AI tools change every month. The principles behind them do not. These courses give you the foundation to understand whatever comes next.