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AB-100 study guide

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Lessons

  1. Agent Behaviors: Multi-Step Reasoning, Voice
  2. Adding Knowledge Sources to In-App Help & Gu
  3. Orchestrating Prebuilt Copilot AI Features i
  4. Orchestrating Prebuilt AI in Dynamics 365 F&
  5. Proposing Microsoft 365 Agents for Business
  6. Designing Task Agents, Autonomous Agents & P
  7. Copilot Studio Topic Design, Trigger Phrases
  8. Orchestration Selection: Standard NLP vs CLU
  9. Computer Use Automation & Web UI Interaction
  10. Microsoft Foundry Custom Models & Foundry To
  11. Agent Extensibility via Model Context Protoc
  12. Access Controls, Role-Based Security & Permi
  13. Agent Identity Architecture, Microsoft Entra
  14. Secure Data Processing & Grounding Data Isol
  15. Microsoft AI Center of Excellence & Solution
  16. Cloud Adoption Framework for Azure AI Strate
  17. Multi-Agent Architecture: Microsoft 365 Copi
  18. Developing Use Cases for Prebuilt Agents & t
  19. Solution Rules & Constraints for Copilot Stu
  20. ALM for Custom AI Models, Fine-Tuning Artifa
  21. ALM for Dynamics 365 AI in Finance, Supply C
  22. ALM for Microsoft Foundry Agents Service & M
  23. ALM for Copilot Studio Agents, Connectors &
  24. ALM for Grounding Data, Vector Indexes & Kno
  25. Environment Strategy & Automated Deployment
  26. Designing Agent Flows & Prompt Actions in Co
  27. Power Apps Canvas App Integration, Generativ
  28. Proposing Microsoft Power Platform AI Featur
  29. Power Platform Well-Architected Framework fo
  30. Business Terms & Copilot Customization in Cu
  31. Agent Integration with Dynamics 365 Contact
  32. Connectors & Data Flow Design for Copilot in
  33. Azure AI Content Safety, Prompt Shields & Gu
  34. Mitigating Prompt Manipulation, Jailbreaks &
  35. Model Security Architecture & Defense Agains
  36. Cross-App AI Strategy for Multi-App Dynamics
  37. Model Selection Strategy, Custom Models & Sm
  38. Enterprise Prompt Engineering Guidelines & P
  39. Assessing Agents for Task Automation, Analyt
  40. Structuring Enterprise Business Data for AI
  41. Grounding Data Evaluation: Accuracy, Relevan
  42. Comprehensive Audit Trails, Model Decision L
  43. Data Residency, Sovereign Boundaries & Cross
  44. Designing Governance for Agents: Environment
  45. Microsoft Responsible AI Standard: Principle
  46. Build vs Buy vs Extend Architectural Decisio
  47. Comprehensive Financial ROI Analysis for Bus
  48. Dynamic Model Router Architecture & Cost-Per
  49. ROI Criteria & Total Cost of Ownership for A
  50. Monitoring Architectures: Azure Monitor, App
  51. Telemetry Data Interpretation, Performance M
  52. User Feedback Analysis, Backlog Prioritizati
  53. Agent Testing Frameworks, Quality Metrics &
  54. Copilot-Assisted Test Case Generation & Cros
  55. Custom AI Model Validation, Safety Criteria
  56. Validating Effective Copilot Prompt Practice