This course teaches developers how to create end-to-end solutions in Microsoft Azure. Students will learn how to implement Azure compute solutions, create Azure Functions, implement and manage web apps, develop solutions utilizing Azure storage, implement authentication and authorization, and secure their solutions by using KeyVault and Managed Identities. Students will also learn how to connect to and consume Azure services and third-party services, and include event- and message-based models in their solutions. The course also covers monitoring, troubleshooting, and optimizing Azure solutions. Develop AI Cloud Solutions on Azure (AI-200) Benefits Course Benefits Build practical generative AI applications using Microsoft Azure technologies Learn to integrate Azure OpenAI models into enterprise applications Develop AI copilots and conversational agents Gain hands-on experience with prompt engineering and orchestration Understand responsible AI implementation and AI safety controls Prepare for modern AI-focused development roles Gain skills aligned with rapidly growing enterprise AI adoption Includes hands-on labs and Microsoft official content Supports hybrid and remote participation through AnyWare® delivery Prerequisites Experience developing software applications Familiarity with Python or C# Basic understanding of cloud computing concepts Basic familiarity with Azure services Understanding of REST APIs and JSON recommended Exam Information This course can help you prepare for the following Microsoft role-based certification exam — Microsoft Certified: Azure AI Cloud Developer Associate (beta) Azure AI Cloud Solutions Training Outline Learning Objectives Get started with Azure AI Foundry Explore Azure AI Foundry capabilities Understand Azure AI Foundry portals and resources Manage AI projects and workspaces Use Azure AI Foundry tools and SDKs Develop generative AI applications with Azure OpenAI Service Provision Azure OpenAI resources Deploy Azure OpenAI models Generate text using prompts Integrate Azure OpenAI into applications Configure model parameters Implement prompt engineering techniques Design effective prompts Apply prompt engineering best practices Control model responses Optimize prompts for business scenarios Build copilots with Azure AI technologies Create conversational AI experiences Develop copilots using Azure AI services Manage conversational flows Integrate AI copilots into applications Implement retrieval-augmented generation solutions Understand retrieval-augmented generation concepts Use vector search capabilities Ground prompts with enterprise data Integrate AI search solutions Develop AI agents and orchestration workflows Create AI orchestration workflows Manage multi-step AI interactions Coordinate AI agents and tools Integrate external services into AI workflows Implement responsible AI practices Understand responsible AI principles Evaluate AI safety considerations Apply content filtering and moderation Mitigate harmful AI outputs Deploy and manage generative AI applications Deploy AI applications in Azure Monitor AI solution performance Manage scalability and governance Secure AI workloads and services
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