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

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Bioinformatics trainees developed an open-source Python curriculum for high school women, using Jupyter notebooks for data science education. This resource offers bite-sized lessons and capstone projects, fostering coding skills in a supportive environment.

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Area of Science:

  • Computer Science Education
  • Bioinformatics
  • Data Science

Background:

  • Lack of tailored resources for teaching introductory data science and Python to high school women.
  • Need for a fun, supportive, and hands-on learning environment.
  • Existing educational materials did not meet specific pedagogical needs.

Purpose of the Study:

  • To develop and share an open-source curriculum for teaching introductory Python for data science.
  • To create an effective instructional format using Jupyter notebooks.
  • To provide a valuable resource for educators and the wider learning community.

Main Methods:

  • Developed a curriculum inspired by The Carpentries organization's model.
  • Utilized Jupyter notebooks for live coding and hands-on practice.
  • Incorporated bite-sized lessons, independent practice, and a capstone project with real-world data.

Main Results:

  • Successfully created a comprehensive curriculum and instructional format over three years.
  • The curriculum effectively teaches introductory Python for data science concepts.
  • The developed resource is available as Open Educational Resources on GitHub.

Conclusions:

  • The developed open curriculum is a valuable asset for educators teaching data science and Python.
  • Encourages wider adoption and community contribution to improve the educational materials.
  • Empowers high school women with essential coding and data science skills.