Aerospace AI Capstone — Secure, Deployable System Design

This capstone course brings together the full learning journey: problem identification, AI foundations, workflow design, secure architecture, governance, and deployment planning. Students apply what they have learned to design a practical AI solution for a real aerospace or safety-critical operational challenge.

Working in a studio-style, hands-on format, students refine their problem statement, clarify success criteria, validate workflow assumptions, and experiment with AI tools and platforms to prototype or simulate elements of their solution. Depending on the use case and data sensitivity, students may work with approved online AI tools, structured AI projects, custom assistants, prompt libraries, workflow prototypes, or conceptual local/on-device deployment plans.

The course requires students to integrate both technical and human-centered design considerations. Students define the AI workflow or agent architecture, data inputs and outputs, human-in-the-loop checkpoints, prescriptive versus descriptive decision boundaries, UI/UX interaction model, deployment environment, monitoring approach, and governance safeguards. They also address risks such as over-reliance, hallucination, data leakage, access control, auditability, and operational failure modes.

Students develop a complete capstone package that can be presented to technical, security, operational, and executive stakeholders. This package includes a pilot-ready AI system design, deployment strategy, governance and monitoring plan, risk mitigation approach, and executive-level implementation narrative.

Example capstone use cases may include automated document review pipelines, requirements traceability support, quality reporting copilots, anomaly triage workflows, secure internal reporting assistants, supply chain monitoring workflows, or operational intelligence dashboards. By the end of the course, students leave with a credible AI solution concept that is practical, governance-aware, and aligned with real aerospace adoption needs.