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Evaluate when to develop custom AI agents tailored to your needs and when to deploy prebuilt solutions from trusted platforms. Learn how to assess trade-offs in time-to-value, complexity, customization, and operational cost. This module also guides you in selecting the right models for your AI agents, from lightweight task-specific agents to advanced multi-modal agents.

Units in this learning path:

• Select AI Service Host Platform
• Custom Built AI Agents
• Evaluate Trade Offs
• Knowledge Check
• Summary

Products: Microsoft Foundry, Foundry Tools, Azure Openai, Ms Copilot

Roles: Developer

Level: Intermediate

Subjects: Artificial Intelligence

Duration: 28 minutes

In this digital learning experience, you will learn the importance of maintaining an SAP clean core when integrating with Amazon Web Services (AWS). You will also explore the capabilities to modernize SAP applications using AWS. The course covers…

Monitor a published agent in Microsoft Copilot Studio, improve it from production evidence, and communicate its value.

Units in this learning path:

• Introduction
• Review Production Health Monitor Tab
• Diagnose Issues Session Evidence
• Improve Agent Session Transcripts
• Extend Monitoring Application Insights
• Communicate Agent Value Telemetry
• Knowledge Check
• Summary

Products: Microsoft Copilot Studio

Roles: Developer, Maker

Level: Intermediate

Subjects: Artificial Intelligence

Duration: 55 minutes

Learn how to monitor using real-time visibility into all agents to detect sprawl, understand usage.

Units in this learning path:

• Introduction
• Introduction Agent Identity
• Monitor Agent
• Observe Agents Scenarios
• Exercise View Agent Overview
• Exercise Explore Agents Inventory
• Exercise Explore Agents Map
• Exercise View Exceptions Delete
• Exercise Measure Effectiveness
• Exercise View Connected Platforms
• Check
• Summary

Products: M365, Agent 365

Roles: Administrator

Level: Intermediate

Subjects: Artificial Intelligence

Duration: 71 minutes

Learn why Microsoft 365 offers several Microsoft Copilot and agent report sources, choose the right one for a given question, reconcile Microsoft 365 and Microsoft Foundry costs without double-counting, and use Microsoft 365 Service Health and Copilot controls to diagnose AI-service issues honestly.

Units in this learning path:

• Introduction
• Pick Right Report Source
• Exercise Pick Right Report Source
• Read Copilot Agent Usage Reports
• Exercise Read Copilot Agent Usage Reports
• Reconcile Copilot Agent Costs
• Exercise Reconcile Copilot Agent Costs
• Optimize AI Spend
• Assess AI Service Health Copilot Control System
• Knowledge Check
• Summary

Products: M365, M365 Admin Center

Roles: Administrator

Level: Intermediate

Subjects: Artificial Intelligence

Duration: 82 minutes

Learn how to monitor the performance of your generative AI application using Microsoft Foundry. This module teaches you to track key metrics like latency and token usage to make informed, cost-effective deployment decisions.

Units in this learning path:

• Introduction
• Why Monitor
• What to Monitor
• How to Monitor
• Prepare Scripts
• Informed Decisions
• Exercise
• Knowledge Check
• Summary

Products: Microsoft Foundry

Roles: AI Engineer

Level: Intermediate

Subjects: Artificial Intelligence, App Development

Duration: 60 minutes

Learn to monitor, analyze, and tune AI agents for reliability, performance, and continuous improvement in enterprise environments.

Units in this learning path:

• Introduction
• Recommend Process Tools Monitoring Agents
• Analyze Backlog User Feedback AI Agent Usage
• Apply AI Based Tools Analyze Identify Issues Perform Tuning
• Monitor Agent Performance Metrics
• Interpret Telemetry Data Performance Model Tuning
• Knowledge Check
• Module Summary

Products: Microsoft 365 Copilot, M365, Microsoft 365 Copilot Chat, Power Platform, Microsoft Copilot Studio

Roles: Database Administrator, Developer, Administrator, Solution Architect, Technology Manager

Level: Advanced

Subjects: Generative AI, Data Analytics, Data Management, Data Engineering, Data Integration

Duration: 36 minutes

Learn how to operate production multi-agent solutions with comprehensive visibility, systematic quality assurance, cost control, and robust incident response. Learners advance from single-application monitoring and evaluation experiments to distributed multi-agent observability, LLM-as-judge evaluation for coordination quality, multi-agent cost optimization, enterprise human-in-the-loop approval workflows, and structured AI incident debugging procedures. AI-500

Modules in this learning path:

• Implement Distributed Observability Multi Agent Opentelemetry
• Design Evaluation Frameworks Multi Agent Azure
• Optimize Multi Agent Performance Cost Azure
• Design Human in Loop Approval Workflows
• Debug Production Multi Agent Incidents Azure

Products: Agent Framework, Azure Cosmos Db, Azure Monitor, Azure Managed Redis, Microsoft Foundry, Office Teams, Power Automate

Roles: AI Engineer, Solution Architect

Level: Advanced

Subjects: Artificial Intelligence

Duration: 203 minutes

This credential earner has applied proficiency in NLP and its role in language understanding, sentiment analysis, and advanced text generation. The individual demonstrated their knowledge on how NLP systems are designed to interpret human language, extract sentiments from textual data, as well as practical experience in NLP techniques and models. The learner is familiar with the skills required for success in a related job role.

Explore the Microsoft Copilot app and its four modes—Chat, Cowork, Code, and Autopilot—and learn when to use each one for your work.

Units in this learning path:

• Introduction
• Copilot Modes Overview
• Knowledge Check
• Summary

Products: Ms Copilot, M365

Roles: Business User

Level: Beginner

Subjects: Artificial Intelligence, Productivity

Duration: 12 minutes

With Amazon SageMaker Canvas, data and business analysts can prepare data, train, and deploy machine learning (ML) models without any ML experience or writing a single line of code. You will learn to build ML models for tabular and time series…

Learn how to instrument distributed applications with OpenTelemetry and analyze telemetry data with Azure Monitor to observe and troubleshoot AI solutions on Azure.

Modules in this learning path:

• Instrument App Opentelemetry
• Analyze Telemetry Logs Metrics

Products: Azure Monitor

Roles: Developer

Level: Intermediate

Subjects: Artificial Intelligence, App Development

Duration: 161 minutes