Microsoft Certified: Azure AI Cloud Developer Associate Certification
The Microsoft Certified: Azure AI Cloud Developer Associate Certification course prepares developers to build, deploy, secure, and monitor AI-powered cloud applications on Microsoft Azure. Participants learn to implement scalable AI solutions using containers, Kubernetes, vector databases, event-driven architectures, serverless computing, and Azure-native services.
This hands-on course focuses on the technologies and development practices required to support modern AI applications while preparing learners for the Microsoft Azure AI Cloud Developer Associate certification.
About this Course
The Microsoft Certified: Azure AI Cloud Developer Associate Certification (AI-200) course is designed for developers responsible for building, deploying, and managing AI-powered applications on Microsoft Azure. Participants learn how to integrate cloud-native services, containerized applications, vector databases, event-driven architectures, and observability tools into scalable AI solutions.
Throughout this five-day instructor-led course, learners will develop practical skills in Azure Kubernetes Service (AKS), Azure Container Apps, Azure Cosmos DB, Azure Database for PostgreSQL, Azure Managed Redis, Azure Service Bus, Azure Event Grid, Azure Functions, Azure Key Vault, and OpenTelemetry.
This course aligns with the responsibilities of an Azure AI Cloud Developer, including solution design, development, deployment, security, monitoring, and operational support of AI applications running in Azure environments
Outline
Day 1: Containerized AI Application Hosting
Learning Path 1: Implement Container Application Hosting on Azure
- Store and manage containers in Azure Container Registry
- Deploy containers to Azure App Service
Learning Path 2: Deploy and Manage Apps on Azure Container Apps
- Deploy containers to Azure Container Apps
- Manage containers in Azure Container Apps
- Scale containers in Azure Container Apps
Day 2: Kubernetes and AI Data Solutions
Learning Path 3: Deploy and Monitor Apps on Azure Kubernetes Service
- Deploy and verify applications on AKS
- Configure applications on AKS
- Monitor and troubleshoot applications on AKS
Learning Path 4: Develop AI Solutions with Azure Cosmos DB for NoSQL
- Build queries for Azure Cosmos DB
- Implement vector search capabilities
- Optimize query performance
Day 3: AI Databases and Caching Technologies
Learning Path 5: Develop AI Solutions with Azure Database for PostgreSQL
- Build and query PostgreSQL databases
- Implement vector search
- Optimize indexing, scaling, and performance
Learning Path 6: Enhance AI Solutions with Azure Managed Redis
- Implement Redis data operations
- Stream and coordinate events
- Implement vector storage solutions
Day 4: AI Backend Services and Security
Learning Path 7: Integrate Backend Services for AI Solutions
- Queue and process AI operations with Azure Service Bus
- Develop event-driven workflows with Azure Event Grid
- Build serverless AI backends using Azure Functions
Learning Path 8: Manage Application Secrets and Configuration
- Secure applications with Azure Key Vault
- Manage application settings using Azure App Configuration
Day 5: Monitoring and Troubleshooting AI Applications
Learning Path 9: Observe and Troubleshoot Applications on Azure
- Instrument applications with OpenTelemetry
- Analyze logs, metrics, and telemetry
- Monitor application health and performance
Prerequisites
To be successful in this course, students should have:
Required Experience
- 1–2 years of professional software development experience
- Experience programming in Python
- Basic understanding of cloud application development
Recommended Certifications
- Microsoft Certified: Azure Fundamentals (AZ-900)
- Microsoft Certified: Azure AI Fundamentals (AI-900)
- Microsoft Certified: Azure Data Fundamentals (DP-900)
Recommended Knowledge
- Azure services and cloud concepts
- Containerization concepts and practices
- Application deployment fundamentals
- Basic database and API development concepts
This course is best suited for:
- Software Developers
- Cloud Developers
- AI Application Developers
- Azure Engineers
- DevOps Professionals
- Solution Architects
- Technical Professionals pursuing the Azure AI Cloud Developer Associate certification
Exam Details
Exam AI-200: Microsoft Certified: Azure AI Cloud Developer Associate Certification
Exam Pass Guarantee
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Christopher Fowler
MCSA
Very thorough, good mix of lecture and lab work. Al is great! Keeps classes interesting and supplements required test material with need-to-know items from real world experience.
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MCSA
Microtrain presents the course material in an interesting and concise manner. Microtrain gives the student all the resources necessary to pass the certification exams. Both the Chicago and Lombard facilities were excellent, and the staff goes to any length to accommodate any student changes.
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