Automate, Analyze, and AI Feedback is an intermediate-level course for MLOps professionals and data scientists who need to build AI systems that do not just launch, but last. In the real world, even the best models degrade over time due to model drift. This course teaches you to combat this by creating automated, self-improving systems that learn from operational experience.

You will learn to design and deploy Human-in-the-Loop (HITL) pipelines that identify low-confidence predictions, route them for expert human review, and schedule automated retraining with the new, high-quality data. Moving beyond simple accuracy, you will master advanced model evaluation techniques. Through hands-on labs, you will generate and analyze Precision-Recall (PR) curves, apply resampling methods to ensure your model generalizes well, and select the optimal decision threshold that balances competing business objectives, like maximizing recall while minimizing false alarms. This course will equip you to build resilient MLOps systems that turn human expertise into a continuous source of model improvement.