Applied GenAI Integration and Deployment

This unit focuses on applying advanced generative AI techniques and tools to real-world problems, emphasizing end-to-end workflows, system integration, and domain-specific considerations (healthcare, finance, education, marketing). Students will refine prompts, assemble deliverables, integrate conversational agents and automation into existing systems, and address security, ethics, and performance measurement in deployment-ready plans.

Learning Objectives

• Analyze and compare at least three GenAI models or tools (e.g., GPT Minis, adjustable model weights, Copilot features) and justify tool selection for two distinct domain use cases based on performance, cost, privacy, and ethical trade-offs
• Apply advanced prompting strategies and supplemental data to produce and render a complete deliverable (such as a long-form article, presentation, or email campaign) that incorporates SEO, visual assets, and Copilot-assisted data visualization or formulas
• Demonstrate integration of a conversational AI or automation solution into an existing system by producing a system diagram, implementing APIs or connectors in a prototype, and documenting at least three data security and privacy controls
• Evaluate limitations, bias, and safety risks of GenAI in contexts like healthcare, education, and finance and design a mitigation plan that includes governance steps, KPI definitions, and accommodations for special education needs