Generative AI MLOps: Deploying and Managing Models with Vertex AI

Deploying generative AI models into production comes with unique operational challenges, from managing massive foundation models to ensuring reliable, safe outputs. This text-based course guides you through the core principles of Machine Learning Operations (MLOps) specifically tailored for generative AI. You will transition from simply writing prompts to building robust, automated pipelines that deploy, monitor, and maintain generative AI applications using Vertex AI. What you'll learn: - Understand the core terminology of MLOps and how it applies to generative AI systems. - Configure model deployment pipelines using Vertex AI to automate your development workflow. - Apply retrieval-augmented generation (RAG) architectures to ground your models in custom data. - Evaluate foundation model performance using modern metrics and systematic testing. - Monitor deployed generative models for drift, latency, and safety in real-world scenarios. - Practice fine-tuning and prompt management strategies to optimize model outputs. The course begins with foundational MLOps concepts and terminology before guiding you through practical deployment strategies, pipeline automation, and model monitoring techniques. You will learn through clear, written explanations and structured text-based exercises. Designed for beginners, this course requires no previous DevOps or advanced machine learning experience, making it ideal for aspiring AI engineers and developers. Start mastering the operational side of generative AI today.