課程名稱：Microsoft Certified AI Transformation Leader 國際認可證書課程 (1 科 AI 轉型)
- 簡稱：Microsoft AI Transformation Training Course |
Exam AB-731: Microsoft Certified AI Transformation Leader
Identify the business value of generative AI solutions
- 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 Microsoft’s AI apps and services
- 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 Foundry Tools, 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 Microsoft’s AI apps and services
- 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 Foundry Tools subscription models, including pay-as-you-go and commitment tiers
The course content above may change at any time without notice in order to better reflect the contents of examination. |
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