Most AI training was built for data scientists or software engineers. The datasets are wrong, the threat model is missing, and the labs end before anything useful for a security practitioner begins. A SOC analyst doesn't need to predict iris species. They need to flag a beaconing C2 channel in a Zeek log. The hands-on AI training market for cybersecurity professionals is small. Here's what actually qualifies and how to evaluate options. What "Hands-On" Should Mean A real hands-on course has you writing and running code from the first hour. Not pseudocode on slides. Not vendor demos. Actual code in a working environment, against data that looks like what you see at work. The tells: Pre-configured environment. A good course ships a VM or container with Jupyter , pandas , scikit-learn , PyTorch or transformers , and realistic security datasets loaded. GTK Cyber students work in the Centaur VM , a free Apache 2.0 portable lab. No setup tax. Security datasets, not Kaggle.…