Systems, Hardware, and Data Harvesting for AI Engineering

3 credits · Undergraduate

Practical and theoretical foundations of deployment of AI systems on embedded systems. Emphasis on data collection (data harvesting), edge-device deployment, system integration, and end-to-end pipeline design for real-world AI applications. No credit for students who have earned credit for ECE 5604. Prerequisites: CS 1100, 1101, 1105, or DS 1100; ECE/CS 2123 or ECE/CS 2281 or ME 2171 or BME 2900W or DS 3100 or CE 2200 or CHBE 2250. [3]