Working with Generative AI Models in Azure Machine Learning

Generative AI is transforming how we build software, but deploying and managing these massive models requires robust cloud infrastructure. Azure Machine Learning provides the enterprise-grade tools needed to transition from experimental prompts to production-ready AI applications. This text-based course guides you through the foundational concepts of generative AI within the cloud ecosystem. You will understand how to select pre-trained models, customize them for specific tasks, and deploy them securely. What you'll learn: • Understand the core architecture of generative AI and large language models • Navigate the model catalog to find and evaluate foundation models • Deploy generative models to cloud endpoints for real-time inference • Apply prompt engineering techniques and implement retrieval-augmented generation (RAG) patterns • Fine-tune models with custom datasets to improve performance • Monitor and evaluate model safety and performance metrics. You will start with key terminology and foundational definitions before progressing to structured written explanations of cloud-based AI workflows. This course is built for beginners, developers, and cloud enthusiasts, with no prior machine learning experience required. Start reading today to build your first generative AI solution in the cloud.