AI & Machine Learning

You've seen the headlines. AI is eating the world. But behind every "AI-powered" product, there's an engineer who actually built the model, trained it, evaluated it, and deployed it. That's what this course teaches you to be. We start where Data Science ends: you already know Python and basic statistics (or you'll pick them up fast in the first two weeks). From there, we go deep into neural networks: how they learn, why they work, and when they don't. Then specialized architectures: CNNs for images, RNNs and Transformers for text, and the attention mechanism that powers every LLM from GPT to Claude. You'll build things. An image classifier that actually works. A sentiment analysis pipeline. A text generator. A recommendation system. Not from tutorials, but from understanding the math, the architecture, and the engineering decisions behind each model. We also cover the practical side that most AI courses skip: how to deploy models, how to monitor them in production, how to handle bias, and how to work with LLMs and the emerging generative AI ecosystem. This is an advanced course. It moves fast. If you want the cutting edge, this is where it lives.