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Ab-731: Ai Transformation Leader
Published 2/2026
Created by Christopher Nett | 80.000+ Enrollments Worldwide
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 51 Lectures ( 4h 52m ) | Size: 1.8 GB[/center]
Pass AB-731 | Elevate your career
What you'll learn
✓ Identify the foundational concepts of generative AI
✓ Identify benefits and capabilities of generative AI solutions
✓ Identify benefits and capabilities of Microsoft 365 Copilot and Microsoft Copilot
✓ Identify benefits and capabilities of Azure AI services
✓ Align an AI strategy with Microsoft responsible AI policies
✓ Plan for AI adoption across the organization
Requirements
● Basic IT Knowledge
● Willingness to learn cool stuff!
Description
This course contains the use of artificial intelligence.
This AB-731 course by Christopher Nett is a meticulously organized Udemy course designed for IT professionals aiming to pass the Microsoft AB-731 exam. This course systematically guides you from the basics to advanced concepts of AI.
By mastering Microsoft AI services, you're developing expertise in essential topics in today's IT and business landscape.
The course is always aligned with Microsoft's latest study guide and exam objectives
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 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 Azure AI services
• Map business processes and use cases to Azure AI services
• Identify capabilities of Azure AI services, including Azure AI Vision, Azure AI Search, and Azure AI Foundry
• Match an AI model to a business need
• Identify the benefits of Azure AI services for generative AI, including scalability and security
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
This course contains promotional materials.
Who this course is for
■ IT Professional
■ IT Manager
■ AI Engineer
■ AI Architect
■ Cloud Engineer
■ Cloud Architect
■ CIO
Ab-731: Ai Transformation Leader
Published 2/2026
Created by Christopher Nett | 80.000+ Enrollments Worldwide
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Level: All Levels | Genre: eLearning | Language: English | Duration: 51 Lectures ( 4h 52m ) | Size: 1.8 GB[/center]
Pass AB-731 | Elevate your career
What you'll learn
✓ Identify the foundational concepts of generative AI
✓ Identify benefits and capabilities of generative AI solutions
✓ Identify benefits and capabilities of Microsoft 365 Copilot and Microsoft Copilot
✓ Identify benefits and capabilities of Azure AI services
✓ Align an AI strategy with Microsoft responsible AI policies
✓ Plan for AI adoption across the organization
Requirements
● Basic IT Knowledge
● Willingness to learn cool stuff!
Description
This course contains the use of artificial intelligence.
This AB-731 course by Christopher Nett is a meticulously organized Udemy course designed for IT professionals aiming to pass the Microsoft AB-731 exam. This course systematically guides you from the basics to advanced concepts of AI.
By mastering Microsoft AI services, you're developing expertise in essential topics in today's IT and business landscape.
The course is always aligned with Microsoft's latest study guide and exam objectives
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 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 Azure AI services
• Map business processes and use cases to Azure AI services
• Identify capabilities of Azure AI services, including Azure AI Vision, Azure AI Search, and Azure AI Foundry
• Match an AI model to a business need
• Identify the benefits of Azure AI services for generative AI, including scalability and security
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
This course contains promotional materials.
Who this course is for
■ IT Professional
■ IT Manager
■ AI Engineer
■ AI Architect
■ Cloud Engineer
■ Cloud Architect
■ CIO
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