The global demand for Artificial Intelligence (AI) talent is growing at a rapid pace, leading to significant AI skills shortages. This experience report describes the creation of a new and uniquely joint-faculty AI concentration within our existing Master's program, characterized by its applied research internship in industry. We describe the experience of creating a multi-disciplinary AI program through broad consultation across two of the largest faculties in our institution. The new concentration has been well-received by the collaborating faculties and with industry partners; its popularity with applicants has resulted in admitting exceptional candidates from around the world and becoming the most popular concentration in the program. We offer this experience report in the hope that it may serve as a model for other practitioners who are considering navigating the creation of a joint-faculty concentration within a graduate program, especially in the popular field of AI.

In this paper, we focus on the certificate redesign of our machine learning program within the context of a three-program bundle; we used an outcome-based approach with the student's targeted career outcome in mind. The purpose of this curriculum redesign is threefold: (1) To align the course content with the industry's rapidly changing needs and demands of the job market; (2) To identify the proper sequence of laddering structure for students taking multiple programs; and (3) To create a natural and streamline flow of the learning experience (i.e., removing overlapping content). We show that the resulting redesign is a holistic set of certificate programs with industry-relevant content tailored for skills-based experiential learning.

Computational thinking is now included in K-5 classrooms and this has led to a demand for new interactive and collaborative learning tools that engage a younger audience. Block-based programming and educational games have both been shown to be effective at engaging children, however they have limitations with respect to supporting collaborative learning and equitable access. Our goal in designing Run, Llama, Run was to build on the positive aspects of block-based programming and educational games while also addressing these limitations. Furthermore, we are using Run, Llama, Run as a platform to explore the trade-offs between digital and tangible interfaces to understand how best to support equitable access while maintaining learning, engagement, and collaboration.