Module 8 Overview#
Theme#
End-to-end AI application
Essential Question#
What evidence shows the application works as a system?
Module Components#
Book prose: conceptual framing, domain scenario, methods, and failure modesAssignment: evidence-backed production of a specific artifactSlides: presentation sequence for seminar or lecture deliveryNarration: spoken version of the slide flowInstructor notes: facilitation plan, discussion prompts, and grading cuesRubric: criteria for evaluating the module artifactNotebook: executable lab aligned with the module theme using synthetic API requests, validation outcomes, latency measurements, and test-case results
Module Artifact#
tested Python AI component with interface contract, CI evidence, and deployment notes focused on end-to-end ai application: Ship a documented AI application with tests and demo data.
Professional Setting#
Students work as if advising an engineering team converting prototype AI code into a maintainable application component. Their work must be intelligible to software engineer, ML engineer, QA lead, product owner, and operations reviewer.