LLM Deployment and Integration on Azure

Integrating AI into cloud environments is a highly sought-after skill, but navigating cloud-based AI services can feel overwhelming. This course demystifies the process of hosting and managing Large Language Models (LLMs) on the Azure platform. You will transition from understanding basic AI concepts to confidently deploying and managing LLMs in the cloud. By reading through structured explanations and analyzing real-world configuration examples, you will learn how to leverage cloud infrastructure to power intelligent applications. What you'll learn: Understand the foundational concepts of Large Language Models and how they operate within cloud environments; Configure Azure OpenAI Service and manage API access securely; Apply prompt engineering techniques to optimize model outputs for specific business tasks; Implement Retrieval-Augmented Generation (RAG) patterns using Azure AI Search to ground models in custom data; Deploy and monitor LLM endpoints to ensure reliable performance and cost efficiency. The course begins with essential terminology and the core architecture of cloud-based language models. You will then progress through step-by-step written guides covering model selection, prompt design, data integration, and secure deployment strategies. This course is designed for software developers, cloud enthusiasts, and technology professionals who are new to AI engineering. No prior experience with machine learning or Azure is required. Start reading today to build your cloud-based AI skillset and deploy your first large language model on Azure.