Exam AB-100 Agentic AI Business Solutions Architect (Video)

Description

• Copyright 2027
• Edition: 1st

• Online Video
• ISBN-10: 0-13-589921-4
• ISBN-13: 978-0-13-589921-2

Master the essential skills and knowledge to become a certified Agentic AI Business Solutions Architect with this comprehensive, hands-on exam preparation course.

The AB-100: Agentic AI Business Solutions Architect Exam video course is designed to empower professionals with the latest knowledge and practical skills required to excel in the rapidly evolving world of AI-driven business solutions. Organizations are increasingly relying on advanced AI technologies to drive innovation and maintain a competitive edge. The demand for experts who can design, architect, implement, and manage agentic AI solutions has never been greater. This course provides an in-depth exploration of agentic AI concepts, frameworks, and best practices, ensuring learners are well-prepared for certification and real-world challenges.

Throughout engaging lectures and demonstrations, learners will gain a comprehensive understanding of how to design and deploy AI solutions that align with business objectives. By the end of the course, participants will have the confidence and expertise needed to pass the AB-100 certification exam and make impactful contributions to their organizations as an AI Business Solutions Architect.                        .

Skill Level:

• Beginner to Early Intermediate

Learn How To:

• Plan AI-powered business solutions by analyzing requirements and defining clear objectives.
• Design an effective overall AI strategy tailored to business needs and goals.
• Evaluate the costs and benefits associated with implementing AI-powered business solutions.
• Develop AI-powered business solutions by designing AI agents and identifying opportunities for solution extensibility.
• Orchestrate and configure prebuilt AI agents and applications to support business processes.
• Deploy and manage AI-powered business solutions, including ongoing analysis, monitoring, and performance tuning.
• Oversee the testing process to ensure AI solutions meet organizational requirements and deliver expected outcomes.
• Design and implement Application Lifecycle Management (ALM) processes specifically for AI-powered business solutions.
• Incorporate responsible AI practices by addressing security, governance, risk management, and compliance considerations throughout the solution lifecycle.

Course requirement:

• Strong understanding of solution architecture principles and best practices
• Proven experience designing and delivering AI-powered business solutions
• Familiarity with Microsoft services and platforms, such as Azure, Power Platform, and Microsoft 365
• Knowledge of integrating multiple technologies to address complex organizational needs
• Experience in implementing scalable and secure solutions
• Ability to foster innovation through technology-driven process improvement
• Basic understanding of data management, security, and compliance in enterprise environments

Who Should Take This Course:

• Solution architects who are responsible for planning, designing, and deploying AI-powered business solutions.
• Business and technology leaders seeking to formulate an effective AI strategy and assess the value of AI investments.
• IT professionals with experience in integrating Microsoft services (e.g., Azure, Power Platform, Microsoft 365) with AI technologies for enterprise-scale projects.
• AI project managers and consultants focused on evaluating solution requirements, costs, and benefits for organizations.
• Developers and technical leads aiming to design, configure, and extend AI agents and prebuilt apps within business solutions.
• Professionals involved in monitoring, testing, and tuning AI-powered solutions to optimize performance and ensure reliability.

About Pearson Video Training:

Pearson publishes expert-led video tutorials covering a wide selection of technology topics designed to teach you the skills you need to succeed. These professional and personal technology videos feature world-leading author instructors published by your trusted technology brands: Addison-Wesley, Cisco Press, Pearson IT Certification, Prentice Hall, Sams, and Que Topics include: IT Certification, Network Security, Cisco Technology, Programming, Web Development, Mobile Development, and more.  Learn more about Pearson Video training at  http://www.informit.com/video.

Video Lessons are available for download for offline viewing within the streaming format. Look for the green arrow in each lesson.

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Sample Content

Table of Contents

Introduction

Module 1: Plan AI-Powered Business Solutions

Lesson 1: Analyze Requirements for AI-Powered Business Solutions

1.1        Assess the use of agents in task automation, data analytics, and decision-making

1.2        Review data for grounding, including accuracy, relevance, timeliness, cleanliness, and availability

1.3        Organize business solution data to be available for other AI systems

Lesson 2: Design Overall AI Strategy for Business Solutions

2.1        Implement the AI adoption process from the Cloud Adoption Framework for Azure

2.2        Design the strategy for building AI and agents in business solutions

2.3        Design a multi-agent solution by using platforms such as Microsoft 365 Copilot, Copilot Studio, and Azure AI Foundry

2.4        Develop the use cases for prebuilt agents in the solution

2.5        Define the solution rules and constraints when building AI components with Copilot Studio, Azure AI services, and Azure AI Foundry

2.6        Determine the use of generative AI and knowledge sources in agents built with Copilot Studio

2.7        Determine when to build custom agents or extend Microsoft 365 Copilot

2.8        Determine when custom AI models should be created

2.9        Provide guidelines for creating a prompt library

2.10     Develop the use cases for customized small language models for the solution

2.11     Provide prompt engineering guidelines and techniques for AI-powered business solutions

2.12     Include the elements of the Microsoft AI Center of Excellence

2.13     Design AI solutions that use multiple Dynamics 365 apps

Lesson 3: Evaluate the Costs and Benefits of an AI-Powered Business Solution

3.1        Select ROI criteria for AI-powered business solutions, including the total cost of ownership

3.2        Create an ROI analysis for the proposed AI solution for a business process

3.3        Analyze whether to build, buy, or extend AI components for business solutions

3.4        Implement a model router to intelligently route requests to the most suitable model

Module 2: Design AI-Powered Business Solutions

Lesson 4: Design AI and Agents for Business Solutions

4.1        Design business terms for Copilot in Dynamics 365 apps for customer experience and service

4.2        Design customizations of Copilot in Dynamics 365 apps for customer experience and service

4.3        Design connectors for Copilot in Dynamics 365 Sales

4.4        Design agents for integration with Dynamics 365 Contact Center channels

4.5        Design task agents

4.6        Design autonomous agents

4.7        Design prompt and response agents

4.8        Propose Microsoft AI services for a given requirement

4.9        Propose code-first generative pages and the use of an agent feed for apps

4.10     Design topics for Copilot Studio, including fallback

4.11     Design data processing for AI models and grounding

4.12     Design a business process to include AI components in a Power Apps canvas app

4.13     Apply the Microsoft Power Platform Well-Architected Framework to intelligent application workloads

4.14     Determine when to use standard natural language processing, Azure conversational language understanding, or generative AI orchestration in Copilot Studio

4.15     Design agents and agent flows with Copilot Studio

4.16     Design prompt actions in Copilot Studio

Lesson 5: Design Extensibility of AI Solutions

5.1        Design AI solutions by using custom models in Azure AI Foundry

5.2        Design agents in Microsoft 365 Copilot

5.3        Design agent extensibility in Copilot Studio

5.4        Design agent extensibility with Model Context Protocol in Copilot Studio

5.5        Design agents to automate tasks in apps and websites by using Computer Use in Copilot Studio

5.6        Design agent behaviors in Copilot Studio, including reasoning and voice mode

5.7        Optimize solution design by using agents in Microsoft 365, including Teams and SharePoint

Lesson 6: Orchestrate Configuration for Prebuilt Agents and Apps

6.1        Orchestrate AI in Dynamics 365 apps for finance and supply chain

6.2        Orchestrate AI in Dynamics 365 apps for customer experience and service

6.3        Propose Microsoft 365 agents for business scenarios

6.4        Orchestrate the configuration of Microsoft 365 Copilot for Sales and Microsoft 365 Copilot for Service

6.5        Propose Microsoft Power Platform AI features, including AI hub

6.6        Design interoperability of the finance and operations agent chats to use additional knowledge sources

6.7        Recommend the process of adding knowledge sources to in-app help and guidance for Dynamics 365 Finance or Dynamics 365 Supply Chain Management apps

Module 3: Deploy AI-Powered Business Solutions

Lesson 7: Analyze, Monitor, and Tune AI-Powered Business Solutions

7.1        Recommend the process and tools required for monitoring agents

7.2        Analyze backlog and user feedback of AI and agent usage

7.3        Apply AI-based tools to analyze and identify issues and perform tuning            

7.4        Monitor agent performance and metrics

7.5        Interpret telemetry data for performance and model tuning

Lesson 8: Manage the Testing of AI-Powered Business Solutions

8.1        Recommend the process and metrics to test agents

8.2        Create validation criteria of custom AI models

8.3        Validate effective Copilot prompt best practices

8.4        Design end-to-end test scenarios of AI solutions that use multiple Dynamics 365 apps

8.5        Build the strategy for creating test cases by using Copilot

Lesson 9: Design the ALM process for AI-Powered Business Solutions

9.1        Design the ALM process for data used in AI models and agents

9.2        Design the ALM process for Copilot Studio agents, connectors, and actions

9.3        Design the ALM process for Azure AI services agents       

9.4        Design the ALM process for custom AI models

9.5        Design the ALM process for AI in Dynamics 365 apps for finance and supply chain

9.6        Design the ALM process for AI in Dynamics 365 apps for customer experience and service

Lesson 10: Design Responsible AI, Security, Governance, Risk Management, and Compliance

10.1     Design security for agents

10.2     Design governance for agents

10.3     Design model security

10.4     Analyze solution and AI vulnerabilities and mitigations, including prompt manipulation

10.5     Review solution for adherence to responsible AI principles

10.6     Validate data residency and movement compliance

10.7     Design access controls on grounding data and model tuning

10.8     Design audit trails for changes to models and data

Summary

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