Teaching Python for Data Science: Collaborative development of a modular interactive curriculum

التفاصيل البيبلوغرافية
العنوان: Teaching Python for Data Science: Collaborative development of a modular interactive curriculum
المؤلفون: Marlena Duda, Kelly Sovacool, Negar Farzaneh, Vy Nguyen, Sarah Haynes, Hayley Falk, Katherine Furman, Logan Walker, Rucheng Diao, Morgan Oneka, Audrey Drotos, Alana Woloshin, Gabrielle Dotson, April Kriebel, Lucy Meng, Stephanie Thiede, Zena Lapp, Brooke Wolford
المصدر: Journal of Open Source Education. 4:138
بيانات النشر: The Open Journal, 2021.
سنة النشر: 2021
الوصف: We are bioinformatics trainees at the University of Michigan who started a local chapter of Girls Who Code to provide a fun and supportive environment for high school women to learn the power of coding. Our goal was to cover basic coding topics and data science concepts through live coding and hands-on practice. However, we could not find a resource that exactly met our needs. Therefore, over the past three years, we have developed a curriculum and instructional format using Jupyter notebooks to effectively teach introductory Python for data science. This method, inspired by The Carpentries organization, uses bite-sized lessons followed by independent practice time to reinforce coding concepts, and culminates in a data science capstone project using real-world data. We believe our open curriculum is a valuable resource to the wider education community and hope that educators will use and improve our lessons, practice problems, and teaching best practices. Anyone can contribute to our Open Educational Resources on GitHub.
تدمد: 2577-3569
DOI: 10.21105/jose.00138
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d5835e2a19b24c7249118262342c3c9d
https://doi.org/10.21105/jose.00138
Rights: OPEN
رقم الانضمام: edsair.doi.dedup.....d5835e2a19b24c7249118262342c3c9d
قاعدة البيانات: OpenAIRE
الوصف
تدمد:25773569
DOI:10.21105/jose.00138