Microsoft AB-731 Exam Syllabus

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Before starting your AB-731 exam preparation, it is recommended to review the complete Microsoft AI Transformation Leader exam syllabus and carefully go through the exam objectives listed below. Once you understand the exam structure and objectives, you should practice using our free AB-731 questions. We also provide premium AB-731 practice test, fully updated according to the latest exam objectives, to help you accurately assess your preparedness for the actual exam.

Microsoft AB-731 Exam Objectives

Section	Weight	Objectives
Identify the business value of generative AI solutions	35-40%	Identify the foundational concepts of generative AI Describe the differences between generative AI and other types of AI Select a generative AI solution to meet a business need Describe the differences between AI models, including fine-tuned and pretrained models Explain the cost drivers in generative AI usage, including tokens and return-on-investment (ROI) considerations Identify the challenges of using generative AI solutions, including fabrications, reliability, and bias Identify when generative AI solutions can provide business value, including scalability and automation Identify benefits and capabilities of generative AI solutions Describe the impact of prompt engineering Understand techniques of prompt engineering Identify business requirements for grounding solutions Understand how retrieval-augmented generation (RAG) is used for AI solutions Understand the impact of data on AI solutions, including data type, data quality, and representative datasets Describe the importance of secure AI Identify scenarios when machine learning adds value Describe the lifecycle of a machine learning solution Identify security considerations for AI systems, including application security, data security, and authentication requirements
Identify benefits, capabilities, and opportunities for Microsofts AI apps and services	35-40%	Identify benefits and capabilities of Microsoft 365 Copilot and Microsoft Copilot Map business processes and use cases to Copilot Understand differences in capabilities between versions of Copilot Understand capabilities of Microsoft 365 Copilot Chat web and mobile experiences Understand capabilities of the Copilot experience in various Microsoft 365 apps Understand capabilities of Microsoft Copilot Studio Understand capabilities of Microsoft Graph Identify benefits and capabilities of an integrated Microsoft AI solution, including risk mitigation and safety benefits Map business processes and use cases to Microsoft’s AI apps and services Identify when to use Researcher or Analyst in Copilot Identify when to build, buy, or extend, including the Microsoft 365 Copilot extensibility framework Identify benefits and capabilities of Foundry Tools Map business processes and use cases to Foundry Tools Identify capabilities of Azure AI services, including Azure Vision in Foundry Tools, Azure AI Search, and Microsoft Foundry Match an AI model to a business need Identify the benefits of Microsoft Foundry and Foundry Tools, including scalability and security
Identify an implementation and adoption strategy for Microsofts AI apps and services	20-25%	Align an AI strategy with Microsoft responsible AI policies Explain the importance of responsible AI Establish governance principles for AI use Establish an AI council to guide strategy, oversight, and cross-functional alignment Ensure that AI solutions meet responsible AI standards, including fairness, reliability, safety, privacy, security, inclusiveness, transparency, and accountability Plan for AI adoption across the organization Establish an adoption team Identify common barriers to adoption Establish an AI champions program Understand potential impacts to data, security, privacy, and cost Understand Copilot license types, including pay-as-you go, monthly, and included with Microsoft 365 subscription Understand Azure AI services subscription models, including pay-as-you-go and prepaid
Official Information		https://learn.microsoft.com/en-us/credentials/certifications/ai-transformation-leader/

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