A meta-repository to help navigate the repos and resources of Girls Who Code at UM-DCMB.
Founded by current doctoral students in the Department of Computational Medicine and Bioinformatics (DCMB) at the University of Michigan, our Girls Who Code club seeks to provide a collaborative and supportive environment for high school women of all skill levels and backgrounds interested in learning how to code.
Due to the research expertise of our graduate student Facilitators, our club curriculum is focused on computational data analysis and the Python programming language. Participants learn core coding concepts and implement their new skills in a data science capstone project of their choosing.
| Repository | Description | Language(s) |
|---|---|---|
| ClubCurriculum | Curriculum for our weekly club for high school students. | |
| SummerExperience | Curriculum for our week-long Data Science Summer Experience. | |
| CapstoneProject | Capstone Project datasets & instructions. | Jupyter Notebook, Python |
| challengeQuestions | Jupyter notebooks of challenge questions for learners. | Jupyter Notebook, Python, Shell |
| codeDemos | Stand-alone Python coding demos. | Jupyter Notebook, Python |
| FEMMES | Resources for activities for U-M FEMMES. | |
| ozobotLessons | Lesson plans for Ozobots. | |
| curriculum-notebooks | Jupyter notebooks for our Summer Experience and Club Curriculum. | Jupyter Notebook, Shell, Python |
| GWC-DCMB | A meta-repository to help navigate our repos and resources. | Python, Shell |
- For contributors, instructors, & facilitators
- For learners
- For everyone
Are you a UMich student, post-doc, faculty, or other member of the University of Michigan community? Join our mailing list or send us an email to find out how you can get involved!
Are you a high school student or younger looking to learn with us? Send us an email and stay tuned to our website for announcements on our next recruiting cycle.
All materials hosted here are subject to the licenses described in the LICENSE file.
The paper describing our curriculum and the development process is out in JOSE! If you would like to cite our work, please use:
Duda & Sovacool et al., (2021). Teaching Python for Data Science: Collaborative development of a modular & interactive curriculum. Journal of Open Source Education, 4(46), 138, https://doi.org/10.21105/jose.00138
A bibtex entry for LaTeX users:
@article{duda_teaching_2021,
doi = {10.21105/jose.00138},
url = {https://doi.org/10.21105/jose.00138},
year = {2021},
publisher = {The Open Journal},
volume = {4},
number = {46},
pages = {138},
author = {Marlena Duda and Kelly Sovacool and Negar Farzaneh and Vy Nguyen and Sarah Haynes and Hayley Falk and Katherine Furman and Logan Walker and Rucheng Diao and Morgan Oneka and Audrey Drotos and Alana Woloshin and Gabrielle Dotson and April Kriebel and Lucy Meng and Stephanie Thiede and Zena Lapp and Brooke Wolford},
title = {Teaching Python for Data Science: Collaborative development of a modular & interactive curriculum},
journal = {Journal of Open Source Education}
}