Abstract:
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There are nation-wide efforts to build data science education capacity outside of traditional curricula. These include not only open source and online educational resources, boot camps, advanced certificates, but also experiential learning programs such as University Washington’s Data Science for the Social Good and Data Science for the Public Good Young Scholars Program at University of Virginia. Pairing student fellows with data scientist mentors and project leads from academia, government, and non-profit organizations. These types of programs serve the dual purposes of advancing projects with positive societal impact and providing real-world data science training for students from diverse disciplinary backgrounds. Integrated stakeholder engagement is a hallmark of these programs.
Leveraging lessons learned from more than 10 university data for good programs, the goals of this session will include surfacing common challenges and better practices across these programs and sharing a roadmap of decision points for organizations interested in designing similar programs. Second, we will draw from these programs to highlight impactful research projects.
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