AI-200T00 | Develop AI cloud solutions on Azure
 
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.
 
Course objectives
Implement container application hosting on Azure using Azure Container Registry and Azure App Service.
Deploy, manage, and scale containerized solutions using Azure Container Apps and Azure Kubernetes Service.
Develop AI solutions that connect to, query, and optimize Azure Cosmos DB for NoSQL, Azure Database for PostgreSQL, and Azure Managed Redis, including vector search for AI workloads.
Connect to and consume Azure services through event- and message-based integration with Azure Service Bus and Azure Event Grid, and build serverless APIs with Azure Functions.
Secure Azure solutions by managing secrets with Azure Key Vault and application settings with Azure App Configuration.
Observe and troubleshoot Azure solutions using OpenTelemetry instrumentation and Kusto Query Language (KQL).
 
Audience Profile
This course is designed for developers who build backend and AI-driven applications on Azure and need practical skills in containerized compute, data services for AI, event-driven workflows, and application security and monitoring.
 
Prerequisites
Fundamental proficiency in app containerization.
Fundamental proficiency in Azure data services.
Fundamental proficiency in AI agents and models.
At least two years of experience in Python.
Familiarity with Azure CLI.
 
Course outline
Learning Path 01: Implement container application hosting on Azure
Learning Path 02: Deploy and manage apps on Azure Container Apps
Learning Path 03: Deploy and monitor applications on Azure Kubernetes Service
Learning Path 04: Develop AI solutions with Azure Cosmos DB for NoSQL
Learning Path 05: Develop AI solutions with Azure Database for PostgreSQL
Learning Path 06: Enhance AI solutions with Azure Managed Redis
Learning Path 07: Integrate backend services for AI solutions
Learning Path 08: Manage application secrets and configuration for AI solutions
Learning Path 09: Observe and troubleshoot apps on Azure
 
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Debido a las constantes actualizaciones de los contenidos de los cursos por parte del fabricante, el contenido de este temario puede variar con respecto al publicado en el sitio oficial, sin embargo, Netec siempre entregará la versión actualizada de éste.