In response to the growing need for socially responsible computer scientists and data scientists, our team is developing a comprehensive data science certificate program specifically tailored for non-computing majors, with a focus on data science for social justice. This program aims to broaden participation in data science and create non-traditional pathways for diverse student populations. Each course in the program is designed to be accessible to non-computing majors, equipping them with the skills to analyze and address social justice issues through data science. Process Oriented Guided Inquiry Learning (POGIL) is employed as an instructional strategy promoting active learning, and real datasets related to social justice are utilized for hands-on activities and assignments, enhancing practical learning experiences. The courses are taught in a synchronous hybrid format, across multiple universities, accommodating both live online and in-person students.

This tutorial will equip educators with the tools to incorporate data science for social justice in their courses. Attendees will have access to materials developed for these courses, enabling them to integrate similar content into their own curricula. A key focus is on recent challenges and opportunities created by generative AI. The presenters will share their experiences, course materials, and strategies for introducing computer science through a social justice lens. Participants will engage in moderated discussions to share ideas and strategies, which will be collated and made available in a shared repository. This initiative aims to enable a wide range of educators to train future generations in data science while addressing social justice issues.