WIP: Python for Everyone as a Mathematics GE Course: Broaden Participation and Enhance Data Science Career Pipeline

This work-in-progress (research-to-practice) paper describes our approach to designing a General Education (GE) Math course, aimed at enabling students not majoring in Computer Science (CS) to learn and apply computer programming in their own fields of study. Research has shown that underrep-resented groups face barriers such as economic and educational disparities, and cultural biases, which limit their access to Data Science (DS) and Artificial Intelligence (AI) education. Given the rapid growth of these technologies, the critical need for a diverse and inclusive workforce is increasingly evident. To address this, educational opportunities tailored for these groups are essential. Our course, Python for Everyone, is a Mathematics/Quantitative Reasoning GE offering and a core requirement for our BS-DS program, designed to meet these needs. It welcomes students from all disciplines, integrating programming skills with mathematical concepts, thereby democratizing access to DS and AI skills, and fostering interdisciplinary collaboration. The course design ensures students from various majors can recognize the relevance and application of computer programming in their fields. This paper delves into the curriculum's theoretical foun-dations, its structure, and the outcomes. Notable achievements include enhanced gender and diversity representation: 39% of the participants were female, surpassing the 25% in traditional CS majors, and the enrollment of underrepresented minority (URM) students reached 19%, compared to 7% in typical CS courses. These outcomes demonstrate the course's effectiveness in fostering diversity, inclusion, and accessibility in DS education. Python for Everyone serves as a pioneering model, guiding students, particularly from underrepresented backgrounds, and providing a pathway to successful careers in DS and AI. Our ongoing efforts involve conducting more surveys and assessments to refine our course, focusing on incorporating more real-world applications to highlight the relevance of DS across disciplines, aiming for a more inclusive workforce, and assessing the impact of this course in enhancing educational and career opportunities for URM students. We believe this paper is a valuable resource for educators dedicated to enhancing GE quantitative reasoning courses and broadening career opportunities in CS, DS, and AI for students from underrepresented groups.