From machine learning basics to building real AI applications — a structured, practical course for curious minds ready to shape tomorrow.
No fluff. No filler. Just the core concepts and hands-on skills that actually matter — taught in a clear, logical sequence.
Understand how machines learn from data. Supervised, unsupervised, and reinforcement learning explained clearly.
Demystify deep learning. Learn how layers, activations, and backpropagation combine to solve complex problems.
Understand transformers, attention mechanisms, and how models like GPT and Claude work under the hood.
Master the craft of communicating with AI models. Design prompts that get reliable, high-quality outputs.
Build a chatbot, image classifier, and recommendation system. Real code, real results, real portfolio pieces.
Navigate bias, fairness, and responsibility. Understand the societal implications of AI systems you'll build.
Each module builds on the last. You'll finish with both deep understanding and practical skills you can use immediately.
History, definitions, and the current AI landscape
Linear algebra, calculus, and probability — just enough
Regression, classification, decision trees, and SVMs
Clustering, dimensionality reduction, and RL basics
Architecture, layers, activation functions, training
CNNs, image classification, object detection
Tokenization, embeddings, transformers
GPT, Claude, Gemini — architecture and application
Zero-shot, few-shot, chain-of-thought techniques
APIs, RAG pipelines, embeddings, deployment
Bias, fairness, alignment, responsible AI
End-to-end AI application from idea to deployment
🔒 30-day money-back guarantee
"This is the clearest, most well-structured AI course I've taken. The math is approachable and the projects are genuinely fun. I got a job as an ML engineer 3 months after finishing."
"I tried 4 other AI courses before this one. None of them explained transformers the way this course does. Module 7 alone was worth the entire price."
"As a product manager, I needed to understand AI without needing to become an engineer. This course gave me exactly that — deep enough to lead technical discussions, accessible enough to not overwhelm."
Former research scientist at DeepMind and Google Brain, Alex has spent 10 years building AI systems and another 5 teaching them. He believes the best way to learn AI is to build things — so every lesson is paired with working code.
His previous course on deep learning has been taken by over 50,000 students worldwide and is consistently ranked among the best technical courses online.