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

The Journal of open source education Pub Date : 2021-01-01 Epub Date: 2021-12-17 DOI:10.21105/jose.00138
Marlena Duda, Kelly L Sovacool, Negar Farzaneh, Vy Kim Nguyen, Sarah E Haynes, Hayley Falk, Katherine L Furman, Logan A Walker, Rucheng Diao, Morgan Oneka, Audrey C Drotos, Alana Woloshin, Gabrielle A Dotson, April Kriebel, Lucy Meng, Stephanie N Thiede, Zena Lapp, Brooke N Wolford
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Abstract

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.

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数据科学 Python 教学:合作开发模块化互动课程。
我们是密歇根大学的生物信息学实习生,在当地成立了 "Girls Who Code "分会,旨在为高中女生提供一个有趣和支持性的环境,让她们学习编码的力量。我们的目标是通过现场编码和动手实践来介绍基本的编码主题和数据科学概念。然而,我们无法找到完全符合我们需求的资源。因此,在过去的三年里,我们开发了一套课程和教学形式,使用 Jupyter 笔记本有效地教授数据科学的 Python 入门课程。这种方法受到了 Carpentries 组织的启发,使用一口式课程,然后利用独立练习时间强化编码概念,最后使用真实世界的数据开展数据科学顶点项目。我们相信,我们的开放式课程对更广泛的教育界来说是一个宝贵的资源,并希望教育工作者能够使用和改进我们的课程、练习题和教学最佳实践。任何人都可以在 GitHub 上为我们的开放教育资源做出贡献。
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