Curriculum Design for a Multidisciplinary Embedded Artificial Intelligence Course: (Abstract Only).

Artificial intelligence (AI) and machine learning are rapidly developing fields, garnering increased attention from the public, as well as academia and industry. Recent advances allow us to use our smart devices at home to control TVs, speakers, and lights. A smart speaker that is plugged into the wall can handle powerful processing that can service complex user requests. However, as we rely more and more on AI conveniences, we expect them to be at our disposal when we are moving around. In this poster, we present preliminary work on the development of a new upper-level undergraduate course open to all computer science, electrical engineering, and applied mathematics students at Wentworth Institute of Technology (WIT). The new course, titled Embedded AI (EAI), introduces topics from embedded systems, artificial intelligence, digital signal processing, linear algebra, and probability and statistics. The proposed course includes lectures introducing the theory behind each topic and laboratory assignments that provide the students with the hands-on experience. At the end of the semester, students develop an embedded AI project of their own. An interdisciplinary academic team of computer scientists and electrical and computer engineers has been working on a curriculum and researching different platforms, datasets and sensors that will ultimately enable students at WIT to develop an embedded device that can support AI tasks as well as give the students the practical skills that employers seek. Handouts will be prepared with sample curriculum and breakdown of topics.