Microsoft Agentic AI Business Solutions Architect (AB-100) Cert Prep by Microsoft Press

Course details

Prepare for the Microsoft Agentic AI Business Solutions Architect (AB-100) certification by discovering the essential skills needed to plan, design, and deploy AI-powered business solutions that drive transformation and innovation within organizational processes. Learn how to architect scalable and secure solutions that integrate multiple Microsoft services to address intricate business challenges. The course covers core areas, including designing an overall AI strategy, evaluating costs and benefits, and ensuring security and compliance. Gain insights into orchestrating configuration, testing, and monitoring AI-powered solutions. Intended for accomplished solution architects, this course gives you the confidence and knowledge to lead AI solutions within your organization. Upon completion, you’ll be more prepared to tackle the intricacies of the AB-100 exam. Whether you're an experienced already or eager to expand your expertise, this course is your gateway to mastering AI-driven business solutions.

Concepts

Introduction

AB-100 agentic AI business solutions architect - Introduction

Analyze Requirements for AI-Powered Business Solutions

Module 1 - Plan AI-powered business solutions introduction
Learning objectives
Assess agents for automation, analytics, and decisions
Review grounding data quality and availability
Organize business data for AI systems

Design Overall AI Strategy for Business Solutions

Learning objectives
Apply the Azure AI adoption process
Design an AI and agent strategy
Design multi-agent solutions with Microsoft platforms
Develop the use cases for prebuilt agents in the solution
Define rules for AI components in Microsoft platforms
Use generative AI and knowledge sources in agents
Choose custom agents or Microsoft 365 Copilot
Determine when custom AI models should be created
Provide guidelines for creating a prompt library
Develop use cases for custom small language models
Use prompt engineering for AI business solutions
Explore the Microsoft AI Center of Excellence
Design AI solutions that use multiple Dynamics 365 apps

Evaluate the Costs and Benefits of an AI-Powered Business Solution

Learning objectives
Select ROI criteria and total cost of ownership
Create an ROI analysis for an AI business process
Decide whether to build, buy, or extend AI components
Route requests to the right AI model

Design AI and Agents for Business Solutions

Module 2 - Design AI-powered business solutions introduction
Learning objectives
Design Copilot business terms in Dynamics 365 apps
Customize Copilot in Dynamics 365 apps
Design connectors for Copilot in Dynamics 365 Sales
Integrate agents with Dynamics 365 Contact Center
Design task agents
Design autonomous agents
Design prompt and response agents
Propose Foundry Tools for a given requirement
Use code-first pages and agent feeds for apps
Design topics for Copilot Studio, including Fallback
Design data processing for AI models and grounding
Add AI components to a Power Apps canvas app
Apply well-architected design to intelligent apps
Choose natural language processing (NLP), conversational language understanding (CLU), or generative AI orchestration
Design agents and agent flows with Copilot Studio
Design prompt actions in Copilot Studio

Design Extensibility of AI Solutions

Learning objectives
Use custom models in Foundry
Design agents in Microsoft 365 Copilot
Design agent extensibility in Copilot Studio
Extend agents with Model Context Protocol (MCP)
Automate app and web tasks with computer use
Design agent reasoning and voice behavior
Optimize agents in Microsoft 365, Teams, and SharePoint

Orchestrate Configuration for Prebuilt Agents and Apps

Learning objectives
Orchestrate AI in finance and supply chain apps
Orchestrate AI for customer experience and service
Propose Microsoft 365 agents for business scenarios
Configure sales solution and service solution in Microsoft 365 Copilot
Propose Power Platform AI features
Extend finance and operations agent chats
Add knowledge sources to Dynamics 365 guidance

Analyze, Monitor, and Tune AI-Powered Business Solutions

Module 3 - Deploy AI-powered business solutions introduction
Learning objectives
Choose tools for monitoring agents
Analyze backlog and user feedback of AI and agent usage
Use AI tools to analyze issues and tune solutions
Monitor agent performance and metrics
Interpret telemetry data for performance and model tuning

Manage the Testing of AI-Powered Business Solutions

Learning objectives
Recommend the process and metrics to test agents
Create validation criteria of custom AI models
Validate effective Copilot prompt best practices
Design end-to-end test scenarios for AI solutions
Build the strategy for creating test cases by using Copilot

Design the Application Lifecycle Management (ALM) Process for AI-Powered Business Solutions

Learning objectives
Design the application lifecycle management (ALM) process for data used in AI models and agents
Design ALM for Copilot Studio agents and connectors
Design the ALM process for Azure AI services agents
Design the ALM process for custom AI models
Design ALM for finance and supply chain AI
Design ALM for customer experience and service AI

Design Responsible AI, Security, Governance, Risk Management, and Compliance

Learning objectives
Design security for agents
Design governance for agents
Design model security
Analyze AI vulnerabilities and prompt manipulation
Review solution for adherence to responsible AI principles
Validate data residency and movement compliance
Design access controls on grounding data and model tuning
Design audit trails for changes to models and data

Conclusion

AB-100 agentic AI business solutions architect - Summary