Optimizing and Deploying Computer Vision Models

Computer vision models require more than accurate architectures—they depend on well-prepared datasets, stable training processes, and reliable evaluation workflows. In this course, you'll learn how to optimize and deploy computer vision models used in real-world AI systems. You’ll start by analyzing computer vision datasets and applying image augmentation techniques to improve model performance and generalization. Next, you'll learn how to evaluate model predictions using task-specific metrics and conduct failure analysis to identify weaknesses in model behavior. The course also explores tec…