This course teaches developers how to create, monitor, and troubleshoot AI solutions on Microsoft Azure. Students will learn how to implement Azure compute and containerization patterns to host applications, build serverless APIs with Azure Functions, and integrate services using event‑driven and message‑based architectures such as Azure Service Bus and Event Grid. The course also covers working with Azure data services that support AI workloads, including designing and querying solutions with Cosmos DB for NoSQL, Azure Database for PostgreSQL with pgvector, and Azure Managed Redis for caching, streaming, and vector search. By the end of the course, developers will be able to connect services, orchestrate AI workflows, and build secure, scalable, and observable AI‑driven applications on Azure.
This learning path guides you through core container hosting workflows on Azure for AI applications and backend services. You use Azure Container Registry to store and organize images, build images in the cloud with ACR Tasks, and apply tagging and versioning practices that support reliable deployments. From there, you deploy custom containers to Azure App Service, configure runtime behavior such as ports, startup commands, and persistent storage, and externalize environment-specific configuration using application settings.
Read More:- https://learn.microsoft.com/en-us/training/courses/ai-200t00