Azure AI and Machine Learning Fundamentals

Building and scaling AI solutions requires more than just algorithms; it requires a robust cloud infrastructure to manage the entire development lifecycle. This course guides you through the process of using Azure services to build, deploy, and maintain intelligent applications in a professional environment. You will transform from a beginner into a practitioner capable of navigating cloud-based data science workflows. By reading through detailed explanations and practicing with written technical scenarios, you will gain the confidence to manage AI projects at scale. What you'll learn: - Understand core AI and machine learning terminology and cloud infrastructure basics - Configure Azure resources specifically optimized for data science and AI workloads - Build and manage end-to-end machine learning pipelines for consistent model training - Deploy models into production environments and establish monitoring for performance - Implement modern Retrieval-Augmented Generation (RAG) patterns and prompt engineering basics - Apply MLOps principles to automate and scale your machine learning experiments The course begins with foundational definitions of cloud computing and AI before moving into the practicalities of resource management, pipeline construction, and modern generative AI patterns. This written program is designed for beginners with no prior cloud experience who want to enter the field of AI engineering. Start building your foundation in cloud-based AI development today.