Module 1 Narration

Module 1 Narration#

Opening#

Open with the professional setting: an engineering team converting prototype AI code into a maintainable application component. 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:

  1. Define Python project structure for AI in the context of Applied AI Programming with Python.

  2. Walk through the lab as a proxy-data exercise, emphasizing what it can and cannot show.

  3. Compare a baseline with an AI-enabled or more sophisticated alternative.

  4. Translate the result into stakeholder language: recommendation, risk, mitigation, and next evidence.

Closing#

Close by returning to the module artifact: tested Python AI component with interface contract, CI evidence, and deployment notes focused on python project structure for ai: Refactor notebook logic into a small package.. Students should leave knowing exactly what artifact they are producing and how it will be judged.