Module 4 Narration#
Opening#
Open with the professional setting: a delivery team deciding whether an AI project should move from experiment to deployment. Ask students what decision is being made, who is affected, and what evidence would be persuasive to a skeptical reviewer.
Middle#
Move through the module in four passes:
Define Evaluation plans and acceptance criteria in the context of AI Project Management & Deployment.
Walk through the lab as a proxy-data exercise, emphasizing what it can and cannot show.
Compare a baseline with an AI-enabled or more sophisticated alternative.
Translate the result into stakeholder language: recommendation, risk, mitigation, and next evidence.
Closing#
Close by returning to the module artifact: deployment decision package with project charter, acceptance gates, risk log, and monitoring plan focused on evaluation plans and acceptance criteria: Define acceptance tests for model and workflow quality.. Students should leave knowing exactly what artifact they are producing and how it will be judged.