Pillars of Program Design and Delivery: A Case Study using Self-Directed, Problem-Based, and Supportive Learning

ABSTRACTAs machine learning (ML) becomes prevalent in industries and businesses, the need to use these algorithms to solve real-world problems grows rapidly. However, there is a serious deficit of qualified talent in this field and thus a corresponding shortage of educational programs. To address the shortage of ML specialists in the field, universities are offering continuing education programs that fast-track the development of technical and transverse skills needed for success in the field. The award-winning machine learning program described in this paper is carefully designed with industry and community partners while focusing on practical skills and participation in the local industry network. This program can be summarized in three learning principles: 1) learners are encouraged to build their knowledge and skills in a self-directed manner; 2) group projects in both simulated and workplace settings are incorporated to support problem-based learning; and 3) supportive learning environment is established to encourage open and safe learning. This paper reports on the instructors' experiences in teaching the four courses based on these principles, which has resulted in high satisfaction from students, successfully placing students in industry, and winning a national award. We offer this experiential report in the hope that it may serve as a point of reference for other instructors and programs for mature technical learners in machine learning.