Presenting Experiential Educational Machine Learning Labs

Yang Liu, Xiaofan Que, Dingrong Wang, Samuel A. Malachowsky, Daniel E. Krutz

Abstract: Artificial intelligence (AI) is becoming increasingly prevalent in our society, leading to a growing demand for a skilled workforce in AI. Unfortunately, this demand remains unmet, particularly among smaller institutions and those serving underrepresented groups, due to resource limitations. This initiative offers two hands-on educational activities in Artificial Intelligence and Machine Learning to facilitate the integration of AI/ML concepts into foundational computing and non-computing courses. While primarily aimed at undergraduate students, the materials created can also benefit high school (grades 9–12) and graduate students in various educational settings, including traditional classrooms and outreach or after-school programs. Labs are accessible through a web browser, making them easy to adopt at all institutions, especially those with limited resources. The self-contained and hosted nature of the labs ensures that they can be adopted by institutions facing resource constraints. The complete project material is publicly available on the project website: https://all.rit.edu