Cloud Computer Vision Fundamentals

Visual data is everywhere, but extracting meaningful insights from images and videos requires the right cloud-based machine learning tools. This course guides you through the process of building, training, and deploying computer vision models on the cloud. You will start with core terminology and fundamental concepts of digital image processing before moving on to practical cloud solutions, ranging from turn-key pre-trained APIs to custom-trained deep learning classifiers. What you'll learn: 1. Understand the fundamentals of digital images, pixel representations, and computer vision terminology. 2. Apply pre-built vision APIs to quickly detect objects, labels, faces, and text within images. 3. Build custom image classification models using cloud-based AutoML and Vertex AI. 4. Configure image preprocessing pipelines and manage datasets for training. 5. Practice deploying trained models to cloud endpoints for real-time predictions. 6. Explore modern vision-language models and vector embeddings for advanced image search. The curriculum begins with essential definitions and foundational theories of computer vision. You will then progress through step-by-step written tutorials that show you how to leverage cloud services for both rapid API integration and custom model development. This text-based course is designed for beginners, developers, and aspiring data scientists who want to learn computer vision on the cloud. No prior machine learning experience is required. Start reading today and learn how to unlock the power of visual data in the cloud.