Author(s):
Recent national challenges have highlighted the nation’s ongoing need for data scientists who can rapidly create actionable results from unprecedented amounts of data being generated in various fields. Computing and mathematics departments in colleges and universities across the U.S. have increased their efforts to provide data science content for their own undergraduate majors, but typically in their senior year. This project has developed a data science curriculum that can attract non-computing majors. Such an option does not require a long prerequisite chain of courses in programming, data structures, and introductory databases, as well as relevant mathematics, make learning more readily-accessible to non-computing majors. The curriculum includes a web-based Data Science Learning Platform (DSLP) for students to obtain hands-on practice with processing and analyzing data without needing to write code, as well as a Data Science Curricular Module (DSCM) that teaches data science concepts in an introductory data science course to students from diverse, non-computing majors.
Coauthors
Erik Golen, Rochester Institute of Technology
