Generative AI Application Development in Azure

Generative AI is transforming how we build software, but moving from a simple prompt to a production-ready application requires a structured engineering approach. This text-based course guides you through the core concepts of designing, building, and deploying intelligent applications using Azure's AI ecosystem. You will transition from understanding basic artificial intelligence concepts to constructing functional, secure, and context-aware generative AI solutions. By focusing on practical design patterns, you will learn how to integrate large language models into software workflows and ground them with custom data. What you'll learn: - Understand foundational generative AI concepts, large language models, and cloud-based AI architecture. - Configure Azure AI services and manage model deployments securely. - Apply prompt engineering techniques to guide model behavior and improve response quality. - Implement Retrieval-Augmented Generation (RAG) patterns to ground models with your own data sources. - Integrate vector database concepts to enable efficient semantic information retrieval. - Evaluate and monitor AI application performance using modern observability principles. The curriculum starts with essential terminology and foundational AI architectures before walking you through model configuration, prompt design, and data integration. You will then explore advanced patterns like RAG and modern evaluation techniques through clear, written explanations and structured code examples. This course is designed for software developers, cloud enthusiasts, and technology professionals who are new to AI development. No prior machine learning or artificial intelligence experience is required, though a basic understanding of general programming concepts is helpful. Start reading today to build your first cloud-based generative AI application.