This page lists exercises associated with Microsoft skilling content on Microsoft Learn
Design stateful agentic loops
Level: 300 | Duration: 90
Design and test stateful agentic loops for the Contoso Capital Investment Research Platform by using Python and Microsoft Foundry.
Exercise Title - Be descriptive.
Level: 100 | Duration: 0
Sentence describing the lab. Include names of key technologies and products
Implement advanced multi-agent orchestration
Level: 300 | Duration: 90
Implement and test advanced multi-agent orchestration for the Contoso Capital Investment Research Platform by using Python and Microsoft Foundry.
Apply task decomposition and collaboration
Level: 300 | Duration: 90
Apply and test task decomposition and agent collaboration for the Contoso Capital Investment Research Platform by using Python and Microsoft Foundry.
Design enterprise agent-to-agent communication
Level: 300 | Duration: 90
Design and test enterprise agent-to-agent communication for the Contoso Capital Investment Research Platform by using Python and Microsoft Foundry.
Design advanced prompting strategies
Level: 300 | Duration: 90
Design and test advanced prompting strategies for the Northwind Health Clinical Intelligence System by using Python and Microsoft Foundry.
Build enterprise tool ecosystems with MCP
Level: 300 | Duration: 90
Build and test an enterprise Model Context Protocol tool ecosystem for the Northwind Health Clinical Intelligence System by using Python and Microsoft Foundry.
Implement advanced RAG with Azure AI Search
Level: 300 | Duration: 90
Implement and test advanced retrieval-augmented generation with Azure AI Search for the Northwind Health Clinical Intelligence System.
Design multi-agent memory architectures
Level: 300 | Duration: 90
Design and test a multi-agent memory architecture for the Northwind Health Clinical Intelligence System by using Python and Microsoft Foundry.
Implement CI/CD for multi-agent systems
Level: 300 | Duration: 90
Implement and test CI/CD controls for the Fabrikam Code Review and Deployment Agent System by using Python and Microsoft Foundry.
Secure multi-agent systems with zero trust
Level: 300 | Duration: 90
Design and test zero-trust security controls for the Fabrikam Code Review and Deployment Agent System by using Python and Microsoft Foundry.
Scale responsible AI governance
Level: 300 | Duration: 90
Design and test responsible AI governance controls for the Fabrikam Code Review and Deployment Agent System by using Python and Microsoft Foundry.
Govern the enterprise agent lifecycle
Level: 300 | Duration: 90
Design and test enterprise agent lifecycle governance for the Fabrikam Code Review and Deployment Agent System by using Python and Microsoft Foundry.
Implement distributed observability
Level: 300 | Duration: 90
Implement and test distributed observability for the Adventure Works Customer Intelligence Platform by using Python, OpenTelemetry, and Microsoft Foundry.
Design multi-agent evaluation frameworks
Level: 300 | Duration: 90
Design and test a multi-agent evaluation framework for the Adventure Works Customer Intelligence Platform by using Python and Microsoft Foundry.
Optimize multi-agent performance and cost
Level: 300 | Duration: 90
Design and test performance and cost controls for the Adventure Works Customer Intelligence Platform by using Python and Microsoft Foundry.
Design human-in-the-loop approval workflows
Level: 300 | Duration: 90
Design and test human-in-the-loop approval workflows for the Adventure Works Customer Intelligence Platform by using Python and Microsoft Foundry.
Debug multi-agent production incidents
Level: 300 | Duration: 90
Diagnose and test multi-agent production incident response for the Adventure Works Customer Intelligence Platform by using Python and Microsoft Foundry.