Getting Started with Vertex AI for Machine Learning

Unlocking the power of machine learning no longer requires managing complex infrastructure from scratch. This text-only course introduces you to Vertex AI, a unified platform designed to streamline the entire machine learning lifecycle from data preparation to model deployment. You will start with the absolute fundamentals, understanding core machine learning terms and cloud concepts before moving on to practical workflows. By reading through clear explanations and studying real-world configuration examples, you will gain the confidence to manage datasets, train models, and deploy scalable endpoints. What you'll learn: - Understand foundational machine learning terminology and the core components of Vertex AI - Prepare and ingest structured and unstructured data for model training - Train models using both automated AutoML pipelines and custom training code - Deploy trained models to scalable endpoints for real-time and batch predictions - Explore generative AI capabilities, including foundation models and prompt engineering basics - Monitor and manage model performance using integrated platform tools This course begins with key definitions and architectural concepts, guiding you step-by-step through dataset preparation, model training options, and deployment strategies. You will learn through detailed written explanations, structured code snippets, and conceptual breakdowns. This course is designed for aspiring data scientists, developers, and cloud enthusiasts who are new to Vertex AI and want a solid, foundational understanding without any prior machine learning platform experience. Start reading today to build and deploy your first cloud-based machine learning model.