Artificial intelligence engineering is most prevalent in systems such as cyber-physical, medical, communication or robotic systems, and devices that can learn from data collected from their environment and adapt their behavior automatically to improve their performance and/or efficiency.

Students will learn the fundamentals of relevant sub-fields in engineering, as well as statistical inference and machine learning. A wide range of additional core and elective courses allow further specialization in more applied areas such as Generative AI, Industrial AI, Robotic Intelligence, Cloud Computing, Ethical and Sustainable AI, Large Language Models, Deep Learning, and more. 

The Engineering AI program is a collaborative effort across the Clark School. Students will have the flexibility to tailor their curriculum through the selection of technical electives toward their background and interests in areas such as Bioengineering, Chemical & Biomolecular Engineering, Civil & Environmental Engineering, Cybersecurity, Cloud Engineering, Data Science & Analytics, Electrical & Computer Engineering, Embedded Systems, Materials Science & Engineering, Mechanical Engineering, Project Management, Reliability, Robotics, Software Engineering, and Systems Engineering.

Graduates from the program will be prepared for professional careers in areas like embedded system design and implementation, industrial and automotive systems engineering, software and data engineering, communications system design, medical signal processing, and beyond.