AB-731 exam prep: Microsoft AI Transformation Leader

Explore what Microsoft Copilot is, its different versions and license types, including Microsoft 365 Copilot and pay-as-you-go options, and how they access work data, memory, and search.

Compare Microsoft 365 license types including personal, family, premium, business basic, standard, premium, and enterprise, highlighting CoPilot features and data grounding limitations.

Explore the differences between Microsoft Co-pilot, Microsoft 365 Co-pilot, and Microsoft 365 Co-pilot chat, including grounding in web, files, work data, and license requirements from personal to enterprise.

Sign up for a free Microsoft 365 business standard trial with monthly billing, requiring a work email, and set up two-factor authentication with Microsoft Authenticator.

Purchase and sign into Microsoft 365 co-pilot, recognizing there is no free trial. Choose a yearly business or enterprise license, assign the license, and wait 24 hours for full access.

Sign in to Microsoft 365 Copilot Chat on web, desktop, and mobile, explore interface and data sources, and see how licenses affect features like chat with an agent and prompts.

Explore Microsoft 365 Copilot Chat, including pages as collaborative canvases and notebooks for context from multiple sources. Learn to create, edit, and share prompts across web and work data modes.

Describe how prompt engineering impacts generative AI in Microsoft 365 Copilot. Craft prompts with goal, context, expectations, and sources to improve accuracy, relevancy, and efficiency.

Learn practical prompt engineering techniques to craft versatile prompts: separate instructions from content, use supporting content, apply chain-of-thought prompting, and employ one-shot to zero-shot learning with imperative and directive guidance.

Identify business requirements for grounding solutions by linking prompts to trusted work data from SharePoint, OneDrive, and Outlook, to reduce fabrication and meet data governance, gdpr, and compliance.

Explore how retrieval augmented generation grounds ai responses by using a search index to fetch contextual data and pre-process chunks into vectors with metadata.

Explore how data shapes AI solutions by comparing structured and unstructured data and evaluating data quality. See how noisy or unrepresentative data degrades prompts and co-pilot outcomes.

Identify the challenges of generative AI, including fabrications, reliability and safety, and bias in training data and image generation.

Learn how secure AI protects work data in Microsoft 365 from leakage and oversharing, while keeping consent intact.

Identify security considerations for AI systems, including application security, prompt injection risks, and deployment and infrastructure risk. Explore authentication requirements and multi-factor options such as MFA, passwordless methods, and FIDO2.

Explore how Microsoft 365 Copilot helps professionals map business processes and use cases to Copilot, with day-in-the-life examples of an operations project manager and a business manager.

Explore how Microsoft Graph connects Microsoft 365 data including users, teams, emails, files, calendar to ground CoPilot with your company data, ensuring security within the Microsoft 365 service boundary.

Learn when to use Researcher versus Analyst in Microsoft 365 Copilot, handling non-structured data like Word and PowerPoint with Researcher, and structured data like spreadsheets with Analyst.

Identify whether to build, buy, or extend using the copilot extensibility framework for Microsoft 365 copilot, including out-of-the-box buy options and custom connectors to ingest external data.

Explore two versions of Microsoft Copilot Studio—lite agent builder and full studio—showing how to attach knowledge, configure instructions, define triggers, and automate tasks with tools, services, and SharePoint/Teams integration.

Explore how Microsoft 365 Copilot in Word drafts, rewrites, and refines articles about the AB731 exam, using prompts, dictation, and image creation.

Learn how the Microsoft 365 Copilot in Excel assists data preparation, cleaning, formula creation, and insights with table data, Copilot suggestions, and automated analyses.

Explore the Copilot experience in Microsoft PowerPoint, from prompt-driven slide creation and structure adjustments to rewriting text, adding images, and summarizing or translating presentations.

Explore how Microsoft 365 Copilot assists in Outlook by summarizing emails, drafting and customizing replies, and scheduling meetings with settable tones and calendar actions.

Explore how Microsoft 365 Copilot in Teams uses a facilitator agent for meetings, providing transcription, notes, decision summaries, open questions, time tracking, and follow-up tasks.

Explore Azure AI services subscription models, including pay-as-you-go and Azure prepayment, with free credits and starter free services. Learn why reservations and saving plans suit dynamic workloads, not AI services.

Describe the differences between generative AI and other types of AI. Generative AI creates multi-modal content from prompts, while traditional AI performs specific tasks and predictive AI forecasts outcomes.

Explore choosing a generative AI solution to meet a business need using co-pilot chat, scheduled prompts, and Microsoft 365 co-pilot, plus building and publishing agents across Teams and other channels.

Explore cost drivers in generative AI, including monthly pricing and token costs, and assess ROI with tangible benefits like labor savings and intangible gains like improved decision making, three times.

Identify when generative AI delivers business value through automation across customer service, marketing, supply chain, HR, and IT, and explore Azure AI benefits like security, governance, and scalability.

Explore Azure Vision, documents and speech capabilities, including OCR and document intelligence for invoices and forms, and image analysis within Microsoft Foundry.

Explore Azure AI Search capabilities, including semantic and vector search, translation, OCR, entity recognition, ingesting data from blob storage, SQL Database, Cosmos DB, Data Lake Storage with Entra ID.

Explore Microsoft Foundry’s capabilities: 11,000+ models to build agents and orchestrate workflows with human-in-the-loop, memory, knowledge grounding with Azure AI search, 1,400+ tools, and PaaS deployment with Azure integration.

Compare AI models by trained tasks, costs, latency, safety, deployment options, including multi-modal processing and retrieval augmented generation, plus region availability. Fine-tune or distill to tailor models to your data.

Explore how Microsoft Foundry AI models match business needs, comparing chat completion and responses with tools like code interpreter and computer use tool, plus embeddings and media generation.

Discover how machine learning adds value by building end-to-end models—from data collection and preparation to training, validation, and interpretation of results—using Azure ML Studio.

Outline an adoption strategy for Microsoft AI apps and services using responsible AI principles. Cover the six principles: fairness, reliability and safety, privacy and security, inclusiveness, transparency, accountability.

Explore governance principles for AI use and how an AI council guides strategy, oversight, and cross-functional alignment through policies, risk management, and diverse, transparent, accountable practices.

Establish an adoption team and AI champions program to drive engagement and transformation aligned with company goals, and overcome barriers like cost and resistance via targeted training.

Explore how data preparation, security measures, privacy controls, and cost considerations shape AI adoption, including data labeling, real-time data, secure transmission, and token-based pricing.

Identify the business value and opportunities of generative AI with Microsoft AI apps and services, then schedule the official exam via Pearson VUE, choosing center or online testing.

Explore the benefits of CorePilot, Generative AI solutions, and Azure AI services, identify foundational concepts of Generative AI, and align an AI strategy with Microsoft-responsible AI policies for organizational adoption.