Developing An Undergraduate ML Course for Non-STEM Students
The artificial intelligence (AI) evolution is reshaping all aspects of human society. Education must evolve at the same time to train the workforce that can design, deploy, manage and develop AI systems. One of the urgent need in AI education is to develop undergraduate Machine learning (ML) courses tailored for non-science-technology-engineering-mathematics (non-STEM) students due to the following reasons. First, ML is the most important and most widely used subset of AI technologies. Second, undergraduate ML courses are currently designed mainly for STEM students, because ML is of interdisciplinary nature heavily involving math and computer programming, in which non-STEM students often lack systematic training. Third, ML also drive the transformation of research and practice in fields such as sociology, history, education, economics and medicine, and in particular, complement or even replace the traditional qualitative research methods in those fields. To address the urgent need, we propose in this project to develop an undergraduate ML course for non-STEM students, without any prerequisite in math and computer programming. Our goal is that from the perspective of practice, non-STEM students shall have the same abilities as STEM students in solving real-world applications using ML toolkits with the help of AI assistants.
