Zhang, Yuanlin, Du, Hanxiang, Staffen, Wendy, Xing, Wanli, and Archer, Joshua. An Integrated Approach to Data Science Foundations in Computing, Mathematics and Statistics. Retrieved from https://par.nsf.gov/biblio/10394972. SIGCSE 2022: The 53rd ACM Technical Symposium on Computer Science Education .
Zhang, Yuanlin, Du, Hanxiang, Staffen, Wendy, Xing, Wanli, & Archer, Joshua. An Integrated Approach to Data Science Foundations in Computing, Mathematics and Statistics. SIGCSE 2022: The 53rd ACM Technical Symposium on Computer Science Education, (). Retrieved from https://par.nsf.gov/biblio/10394972.
Zhang, Yuanlin, Du, Hanxiang, Staffen, Wendy, Xing, Wanli, and Archer, Joshua.
"An Integrated Approach to Data Science Foundations in Computing, Mathematics and Statistics". SIGCSE 2022: The 53rd ACM Technical Symposium on Computer Science Education (). Country unknown/Code not available. https://par.nsf.gov/biblio/10394972.
@article{osti_10394972,
place = {Country unknown/Code not available},
title = {An Integrated Approach to Data Science Foundations in Computing, Mathematics and Statistics},
url = {https://par.nsf.gov/biblio/10394972},
abstractNote = {},
journal = {SIGCSE 2022: The 53rd ACM Technical Symposium on Computer Science Education},
author = {Zhang, Yuanlin and Du, Hanxiang and Staffen, Wendy and Xing, Wanli and Archer, Joshua},
}
Warning: Leaving National Science Foundation Website
You are now leaving the National Science Foundation website to go to a non-government website.
Website:
NSF takes no responsibility for and exercises no control over the views expressed or the accuracy of
the information contained on this site. Also be aware that NSF's privacy policy does not apply to this site.