Finally understand how AI actually works

If you've ever nodded along in a meeting while someone talked about embeddings or RAG or transformer architectures — and then quietly Googled them afterwards — I built this course for you.

There's nothing wrong with that experience. AI has moved extraordinarily fast, and the explanations that exist online tend to be either so technical they assume a computer-science background, or so shallow they leave you with nothing more than a few buzzwords and a vague sense of optimism. Neither is actually useful. What you need — what most people need — is someone to sit down with you and explain it clearly, in the right order, at the right depth. That's what I've tried to do here.

This course covers everything I think an intelligent, curious non-engineer needs to genuinely understand AI. We start at the beginning: Alan Turing, the dream of thinking machines, the long decades of symbolic AI and expert systems, the AI winters when the field nearly collapsed under the weight of its own promises. We work our way forward through the rise of machine learning and deep learning, and we arrive at the transformer architecture and the large language models that are reshaping how knowledge work gets done. The history isn't just background colour — it's where the intuition lives. Once you understand why previous approaches failed, today's systems make sense in a way they simply don't without that context.

From there, we get into how these systems actually work: what machine learning really is (it's simpler than you think, and stranger), what a neural network is doing when it processes your words, what the difference between training and inference means for how you use and trust these tools, and why hallucinations aren't a bug that's about to be fixed — they're a consequence of how the systems are built. We finish with the language of AI: tokens, embeddings, context windows, RAG, fine-tuning, agents, multimodal models. Not the glossary definitions — the real explanations.

I want you to finish this course and feel the difference immediately. Not just in conversations about AI, but in how you read product announcements, evaluate vendor claims, and think about where these tools are genuinely useful versus where they're being oversold. That critical, grounded perspective is rare, and it's more valuable than knowing any particular prompt trick.

If you've been waiting until you had time to "really learn this stuff" — this is that time, and this is that course. Come in curious. You'll leave genuinely informed.