Applied AI Engineering

Catalog description

This capstone course requires students to integrate and apply engineering knowledge from mathematics, programming, data engineering, machine learning, deep learning, and software engineering to design, validate, and deploy an AI‑enabled system that addresses a real‑world problem. Learners work through the full AI system lifecycle, including problem formulation, model development, testing, deployment, and monitoring. The course emphasizes ethical and responsible AI practices, systematic evaluation using appropriate metrics, and production deployment using industry‑standard MLOps tools such as cloud infrastructure, containerization, CI/CD pipelines, and monitoring frameworks. Through this culminating experience, learners demonstrate the ability to design and deploy AI solutions that meet technical, ethical, and operational constraints expected of entry‑level AI engineers.