Microsoft

Develop AI Cloud Solutions on Microsoft Azure AI-200

Learn how to create, monitor, and troubleshoot AI solutions on Microsoft Azure.

  • 2 upcoming dates 2 open for booking
  • $2,995 per seat

Upcoming dates

Dates Where Status Seat Book
Oct 5–9 2026 Live Online 6:00 AM to 2:00 PM PT Confirmed to run Partner led $2,995
Dec 7–11 2026 Live Online 6:00 AM to 2:00 PM PT Confirmed to run Partner led $2,995

See every class on the schedule

About this class

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.

Who Should Attend?

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.

What you'll be able to do

  • Store and manage containers in Azure Container
  • Deploy containers to Azure App Service
  • Deploy containers to Azure Container Apps
  • Manage containers in Azure Container Apps
  • Scale containers in Azure Container Apps
  • Deploy applications to Azure Kubernetes Service
  • Configure applications on Azure Kubernetes
  • Monitor and troubleshoot applications on Azure
  • Build queries for Azure Cosmos DB for NoSQL
  • Implement vector search on Azure Cosmos DB for
  • Optimize query performance for Azure Cosmos DB
  • Build and query with Azure Database for
  • Implement vector search with Azure Database for
  • Optimize vector search in Azure Database for
  • Implement data operations in Azure Managed Redis
  • Implement event messaging with Azure Managed
  • 17 - I mplement vector storage in Azure Managed
  • Queue and process AI operations with Azure
  • Develop event - driven AI workflows with Azure
  • Build serverless AI backends with Azure Functions
  • Manage application secrets with Azure Key Vault
  • Manage application settings with Azure App
  • Instrument an app with OpenTelemetry
  • Analyze app telemetry with logs and metrics

Course outline

  1. Module 1Store and manage containers in Azure Container

    • Registry
    • Registries, repositories, and artifacts
    • Build and run images with ACR Tasks
  2. Module 2Deploy containers to Azure App Service

    • Deploy containers to Azure App Service
    • Configure container runtime behavior
    • Module assessment
    • Observe and troubleshoot containerized apps
    • Module assessment
  3. Module 3Deploy containers to Azure Container Apps

    • Explore Container Apps environments
    • Deploy a container app using the Azure CLI and YAML
    • Configure runtime settings with environment variables and secrets
    • Configure image pull authentication for private registries
    • Verify deployments with logs and status
    • Module assessment
  4. Module 4Manage containers in Azure Container Apps

    • Update images and manage revisions safely
    • Manage the container app lifecycle
    • Monitor logs and troubleshoot issues
    • Configure health probes and troubleshoot failures
    • Optimize container resources and scaling
    • Module assessment
  5. Module 5Scale containers in Azure Container Apps

    • Configure scale rules
    • Implement event - driven scaling with KEDA
    • Apply KEDA scalers for custom workloads
    • Select compute resources for performance and cost
    • Choose and apply revision modes
    • Module assessment
  6. Module 6Deploy applications to Azure Kubernetes Service

    • Create Kubernetes deployment manifests
    • Expose applications in Azure Kubernetes Services
    • Deploy applications to Azure Kubernetes Services
    • Module assessment
  7. Module 7Configure applications on Azure Kubernetes

    • Service
    • Define ConfigMaps for application settings
    • Implement secrets for sensitive data
    • Attach persistent storage to an app
    • Module assessment
  8. Module 8Monitor and troubleshoot applications on Azure

    • Kubernetes Service
    • Monitor application logs and metrics
    • Troubleshoot pods and services
    • Verify service connectivity and endpoints
    • Module assessment
  9. Module 9Build queries for Azure Cosmos DB for NoSQL

    • Explore Azure Cosmos DB for NoSQL
    • Implement the Azure Cosmos DB for NoSQL SDK
    • Query Azure Cosmos DB for NoSQL
    • Module assessment
  10. Module 10Implement vector search on Azure Cosmos DB for

    • NoSQL
    • Store and retrieve embeddings in Azure Cosmos DB
    • Execute vector similarity queries for semantic search
    • Combine vector similarity results with metadata filtering
    • Use the change feed to trigger embedding refresh
    • Module assessment
  11. Module 11Optimize query performance for Azure Cosmos DB

    • for NoSQL
    • Understand indexes in Azure Cosmos DB
    • Configure range and composite indexes
    • Tune vector indexes for embedding workloads
    • Reduce RU costs with strategic indexing
    • Choose consistency levels for optimal performance
    • Module assessment
  12. Module 12Build and query with Azure Database for

    • PostgreSQL
    • Explore Azure Database for PostgreSQL
    • Connect to PostgreSQL
    • Create and manage schemas
    • Query data
    • Integrate SDKs and applications
    • Module assessment
  13. Module 13Implement vector search with Azure Database for

    • PostgreSQL
    • Store and query embeddings with pgvector
    • Perform fast vector similarity search
    • Manage index lifecycle and embedding updates
    • Run vector similarity search for semantic retrieval
    • Implement retrieval patterns for RAG pipelines
    • Module assessment
  14. Module 14Optimize vector search in Azure Database for

    • PostgreSQL
    • Tune PostgreSQL for pgvector
    • Choose and configure vector indexes
    • Optimize data layout
    • Scale for high- volume workloads
    • Connection optimization
    • Module assessment
  15. Module 15Implement data operations in Azure Managed Redis

    • Explore Azure Managed Redis
    • Client libraries and development best practices
    • Implement data operations
    • Module assessment
  16. Module 16Implement event messaging with Azure Managed

    • Redis
    • Publish and subscribe to events with Redis pub/sub
    • Implement task queues with Redis Streams
    • Choose between broadcast and coordinated distribution
    • Module assessment
  17. Module 1717 - I mplement vector storage in Azure Managed

    • Redis
    • Index and query vector data
    • Choose vector types and indexing strategies
    • Optimize Redis data structures for vector storage
    • Module assessment
  18. Module 18Queue and process AI operations with Azure

    • Service Bus
    • Explore Azure Service Bus concepts and messaging in AI architectures
    • Choose between queues and topics with subscriptions
    • Structure messages for AI workloads
    • Process messages reliably
    • Module assessment
  19. Module 19Develop event - driven AI workflows with Azure

    • Event Grid
    • Understand Azure Event Grid concepts and event - driven patterns for AI solutions
    • Work with event schemas and properties
    • Configure delivery and retry policies for reliable event processing
    • Publish custom events from AI applications
    • Module assessment
  20. Module 20Build serverless AI backends with Azure Functions

    • Understand Azure Functions hosting and scaling for AI workloads
    • Set up the local development environment for Functions
    • Create triggers and bindings for AI integration patterns
    • Manage secrets and configuration in Functions
    • Configure identity and access for Functions
    • Module assessment
  21. Module 21Manage application secrets with Azure Key Vault

    • Store and organize secrets, keys, and certificates
    • Retrieve secrets using Azure SDK client libraries
    • Handle secret versioning and rotation
    • Implement caching strategies to reduce Key Vault calls
    • Module assessment
  22. Module 22Manage application settings with Azure App

    • Configuration
    • Connect to App Configuration from application code
    • Organize settings with labels and feature flags
    • Reference Key Vault secrets from App Configuration
    • Decide what to store in App Configuration vs Key Vault
    • Module assessment
  23. Module 23Instrument an app with OpenTelemetry

    • Explore OpenTelemetry and its role in observability
    • Add the OpenTelemetry SDK to an application
    • Configure spans and traces
    • Export telemetry to Azure Monitor
    • Debug distributed flows with trace data
    • Module assessment
  24. Module 24Analyze app telemetry with logs and metrics

    • Write basic KQL queries
    • Explore logs for errors and performance
    • Build dashboards for app telemetry
    • Create workbooks for interactive analysis
    • Set alerts for app failures and anomalies
    • Module assessment

Download the full outline (PDF)

Who this is for

  • 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.

Run this for a team

Private cohorts run on your dates, at your site or online, with the labs pointed at your environment. Above about four people it usually costs less than buying seats.

Or call 916-920-1700, weekdays 8 to 5 Pacific.

More ai classes

See all
Accelerated Delivery Using AI
Other ISI-1616

Accelerated Delivery Using AI

Accelerated Delivery using AI teaches you to leverage AI tools to boost productivity.

  • $1,350 per seat
Next: Nov 3–5 Confirmed to run
Advanced Prompt Engineering & Evaluation
Other ISI-1618

Advanced Prompt Engineering & Evaluation

Go beyond basic prompting to master advanced techniques for enterprise AI deployment.

  • $1,895 per seat
Dates on request
Agentic AI & Workflow Orchestration
Other ISI-1619

Agentic AI & Workflow Orchestration

Through labs and a capstone project, students will develop a complete agent proof-of-concept.

  • $1,895 per seat
Dates on request