Module 3 Narration#
Opening#
Open with the professional setting: a product team evaluating an NLP workflow before using it in customer-facing communication. 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 Language modeling foundations in the context of Natural Language Processing.
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: NLP evaluation packet with task framing, retrieval/evaluation design, and deployment guardrails focused on language modeling foundations: Evaluate next-token predictions and failure modes.. Students should leave knowing exactly what artifact they are producing and how it will be judged.