MLOps with Vertex AI: Model Evaluation Foundations

Building a machine learning model is only half the battle; ensuring it performs reliably in production requires robust evaluation and continuous monitoring. This text-based course guides you through the foundational principles of Machine Learning Operations (MLOps) using Vertex AI. You will transition from simply training models to systematically assessing their performance, identifying biases, and tracking key metrics to ensure high-quality deployments. What you'll learn: - Understand core MLOps concepts and the model evaluation lifecycle - Configure Vertex AI evaluation pipelines to automate performance testing - Analyze key evaluation metrics for classification, regression, and forecasting models - Identify model bias and assess fairness using modern evaluation techniques - Monitor models for data drift and concept drift to maintain accuracy over time - Implement version control and tracking for machine learning experiments The course begins with essential MLOps terminology and foundational evaluation theory before walking you through step-by-step written explanations on configuring and running evaluation tasks. Designed for aspiring ML engineers, data scientists, and developers new to operations, this course requires only basic machine learning knowledge and no prior cloud operations experience. Start mastering the art of model evaluation and elevate your MLOps workflow today.