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Mini-lessons

ADOBE-ACP-PS · Visual communication

Hierarchy guides attention

…sage importance Hierarchy guides attention toward the most important content and actions.

AI-102 · Azure AI application concepts

Choose the AI capability for the task

…monstration does not establish reliable performance across the application's real users and conditions. Worked example An Azure application needs text extracted from scanned invoices. Which …

AI-102 · Generative AI systems

Grounding supplies context, not a guarantee

A generative model produces output based on its learned patterns and the context it receives. Retrieval can supply relevant documents, but the model may still misunderstand or invent details…

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AI-102 · Responsible AI evaluation

Evaluate failures for the people affected

…rs. What should be evaluated? Performance and harms across relevant subgroups Aggregate metrics can conceal uneven impacts. Subgroup analysis reveals disparities needing investigation.

AI-103 · AI security boundaries

AI security boundaries

…eration. Removing citations afterward cannot undo disclosure through the answer. Model output is not inherently trusted code. Execution isolation, explicit capabilities and action validation…

AI-103 · Application and API design

Make service contracts explicit

…Validate data at the boundary and keep authorization close to the protected operation. A timeout can occur after a server completed a request, so retry design must account for uncertain outc…

AI-103 · Azure AI application concepts

Choose the AI capability for the task

…monstration does not establish reliable performance across the application's real users and conditions. Worked example An Azure application needs text extracted from scanned invoices. Which …

AI-103 · Generative AI systems

Grounding supplies context, not a guarantee

A generative model produces output based on its learned patterns and the context it receives. Retrieval can supply relevant documents, but the model may still misunderstand or invent details…

AI-200 · AI security boundaries

AI security boundaries

…eration. Removing citations afterward cannot undo disclosure through the answer. Model output is not inherently trusted code. Execution isolation, explicit capabilities and action validation…

AI-200 · Application and API design

Make service contracts explicit

…Validate data at the boundary and keep authorization close to the protected operation. A timeout can occur after a server completed a request, so retry design must account for uncertain outc…

AI-200 · Azure AI application concepts

Choose the AI capability for the task

…monstration does not establish reliable performance across the application's real users and conditions. Worked example An Azure application needs text extracted from scanned invoices. Which …

AI-200 · Generative AI systems

Grounding supplies context, not a guarantee

A generative model produces output based on its learned patterns and the context it receives. Retrieval can supply relevant documents, but the model may still misunderstand or invent details…

AI-300 · Data pipeline design

Design pipelines for recovery and replay

…ial results, so decide how processing resumes without losing or duplicating records. Track source identity and transformation versions for traceability. Validate the output's business meanin…

AI-300 · Databricks lakehouse concepts

Improve data quality through explicit layers

…ve enough source context to replay processing and diagnose errors. Transactional table features help manage changes, while pipeline design still determines how duplicates, schema evolution a…

AI-300 · Machine-learning engineering

Prevent leakage across the training boundary

…me-series prediction uses a random train/test split across all dates. What alternative better tests future performance? A chronological split respecting prediction time Temporal validation r…

AI-300 · Responsible AI evaluation

Evaluate failures for the people affected

…rs. What should be evaluated? Performance and harms across relevant subgroups Aggregate metrics can conceal uneven impacts. Subgroup analysis reveals disparities needing investigation.

AI-500 · AI security boundaries

AI security boundaries

…eration. Removing citations afterward cannot undo disclosure through the answer. Model output is not inherently trusted code. Execution isolation, explicit capabilities and action validation…

AI-500 · Application and API design

Make service contracts explicit

…Validate data at the boundary and keep authorization close to the protected operation. A timeout can occur after a server completed a request, so retry design must account for uncertain outc…

AI-500 · Azure AI application concepts

Choose the AI capability for the task

…monstration does not establish reliable performance across the application's real users and conditions. Worked example An Azure application needs text extracted from scanned invoices. Which …

AI-500 · Generative AI systems

Grounding supplies context, not a guarantee

A generative model produces output based on its learned patterns and the context it receives. Retrieval can supply relevant documents, but the model may still misunderstand or invent details…