Applied AI Integration and Deployment

This capstone unit guides learners to apply advanced generative AI techniques across real-world domains and workflows, integrating conversational agents, Copilot features, and sensor/automation systems into existing environments. Students will practice tool selection, prompt engineering, data visualization, performance measurement, and develop deployment-ready solutions that address security, ethical, and accessibility concerns.

Learning Objectives

• Analyze and justify the selection of GenAI models, Copilot features, and toolchains for specific domain scenarios (e.g., healthcare, finance, education, marketing) based on accuracy, cost, data sensitivity, and limitations
• Apply advanced prompt engineering and Copilot-assisted workflows to create, refine, and render professional artifacts (presentations, long-form content, emails, formulas, visual assets) that meet defined quality criteria
• Design and demonstrate an integrated conversational AI prototype or automated workflow that connects to existing systems or sensors, implements data security best practices, and measures performance using defined key performance indicators (KPIs)
• Evaluate ethical, legal, and reliability risks (bias, hallucination, privacy, accessibility) and produce mitigation strategies, documentation, and deployment-ready recommendations