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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...

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By Request
$2,995 USD
Duration 5 days
Course Code AI-200T00
Available Formats Classroom

Overview

Course Description

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.

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.

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Course Details

Course Details

Outline

  • Store and manage containers in Azure Container Registry
    • Registries, repositories, and artifacts
    • Build and run images with ACR Tasks
    • Tag and version images
    • Exercise - Build and manage a container image with ACR Tasks
    • Module assessment
  • Deploy containers to Azure App Service
    • Deploy containers to Azure App Service
    • Configure container runtime behavior
    • Configure application settings
    • Observe and troubleshoot containerized apps
    • Exercise - Deploy a container to Azure App Service
    • Module assessment
  • Deploy 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
    • Exercise - Deploy a containerized backend API to Container Apps
    • Module assessment
  • Manage 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
    • Exercise - Diagnose and fix a failing deployment
    • Module assessment
  • Scale 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
    • Exercise - Configure autoscaling using KEDA triggers
    • Module assessment
  • Deploy applications to Azure Kubernetes Service
    • Create Kubernetes deployment manifests
    • Expose applications in Azure Kubernetes Services
    • Deploy applications to Azure Kubernetes Services
    • Exercise - Deploy an AI inference API to Azure Kubernetes Service
    • Module assessment
  • Configure applications on Azure Kubernetes Service
    • Define ConfigMaps for application settings
    • Implement secrets for sensitive data
    • Attach persistent storage to an app
    • Exercise - Configure apps on Azure Kubernetes Service
    • Module assessment
  • Monitor and troubleshoot applications on Azure Kubernetes Service
    • Monitor application logs and metrics
    • Troubleshoot pods and services
    • Verify service connectivity and endpoints
    • Exercise - Troubleshoot apps on Azure Kubernetes Service
    • Module assessment
  • Build 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
    • Exercise - Build a RAG document store on Azure Cosmos DB for NoSQL
    • Module assessment
  • Implement 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
    • Exercise - Build a semantic search application with Azure Cosmos DB for NoSQL
    • Module assessment
  • Optimize 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
    • Exercise - Optimize query performance with vector indexes on Azure Cosmos DB for NoSQL
    • Module assessment
  • Build 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
    • Exercise - Build an agent tool backend on Azure Database for PostgreSQL
    • Module assessment
  • Implement 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
    • Exercise - Implement vector search on Azure Database for PostgreSQL
    • Module assessment
  • Optimize 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
    • Exercise - Optimize vector search performance in Azure Database for PostgreSQL
    • Module assessment
  • Implement data operations in Azure Managed Redis
    • Explore Azure Managed Redis
    • Client libraries and development best practices
    • Implement data operations
    • Exercise - Perform data operations in Azure Managed Redis
    • Module assessment
  • Implement 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
    • Exercise - Publish and subscribe to events in Azure Managed Redis
    • Module assessment
  • Implement vector storage in Azure Managed Redis
    • Index and query vector data
    • Choose vector types and indexing strategies
    • Optimize Redis data structures for vector storage
    • Exercise - Implement semantic search in Azure Managed Redis
    • Module assessment
  • Queue 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
    • Exercise - Process messages with Azure Service Bus
    • Module assessment
  • Develop 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
    • Exercise - Publish and receive events with Azure Event Grid
    • Module assessment
  • Build 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
    • Exercise - Create an MCP server with Azure Functions
    • Module assessment
  • Manage 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
    • Exercise - Manage secrets with Azure Key Vault
    • Module assessment
  • Manage 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
    • Exercise - Retrieve settings and secrets from Azure App Configuration
    • Module assessment
  • Instrument 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
    • Exercise - Instrument an app with the OpenTelemetry SDK
    • Module assessment
  • Analyze 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
    • Exercise - Query logs with KQL
    • Module assessment

Schedule

Upcoming Course Dates

There are currently no scheduled dates for this course. If you are interested in this course, contact us with the form below.

Contact Information
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FAQ

How do I get a Microsoft exam voucher?

Pearson Vue Exam vouchers can be requested and ordered with your course purchase or can be ordered separately by clicking here.

  • Vouchers are non-refundable and non-returnable. Vouchers expire 12 months from the date they are issued unless otherwise specified in the terms and conditions.
  • Voucher expiration dates cannot be extended. The exam must be taken by the expiration date printed on the voucher.

Do Microsoft courses come with post lab access?

Most Microsoft official courses will include post-lab access ranging from 30 to 180 calendar days after instructor led course delivery. A lab training key in class will be provided that can be leveraged to continue connecting to a remote lab environment for the individual course attendee.

Does the course schedule include a Lunchbreak?

Lunch is normally an hour-long after 3-3.5 hours of the class day.

What languages are used to deliver training?

Microsoft courses are conducted in English unless otherwise specified.

Reviews

This course gave me a clearer understanding of the AWS cloud architecture.

This is my second course with ExitCertified. This course exceeded my expectations. The teacher was great and the class was fun.

The class was very vast paced however the teacher was very good at checking in on us while giving us time to complete the labs.

ExitCertified gave a great course on AWS that covered all of the basics in depth with good lab materials.

this class was informative, made me think about certifying for the suse manager cert.