Bootstrap:Data Science
What factors make some people live longer than others? Are more expensive restaurants really better? Is voter fraud a problem? What data would you need to gather to answer these questions, and how would you measure that data to get your answer? Answering real questions in the world involves analyzing data large datasets, from sports stats to record sales to census information.
In Bootstrap:Data Science, students form their own questions about the world around them, analyze data using multiple methods, and write a research paper about their findings. The module covers functions, looping and iteration, data visualization, linear regression, and more. Social studies, science, and business teachers can utilize this module to help students make inferences from data. Math teachers can use this module to introduce foundational concepts in statistics, and it is aligned to the Data standards in CS Principles.
The final project in Bootstrap:Data Science can be used as the Create Task for AP CS Principles!
You can also find previous versions:
Fall 2020,
Spring 2020,
Fall 2019,
Spring 2019,
Fall 2018,
Spring 2018 and
Spring 2017.
Learn More
Bootstrap is the first national provider to offer an introductory Data Science course. See our
blog post for the design principles that underlie our approach.

Bootstrap:Data Science by Emmanuel Schanzer, Nancy Pfenning, Emma Youndtsmith, Jennifer Poole, Shriram Krishnamurthi, Joe Politz and Ben Lerner was developed partly through support of the National Science Foundation, (awards 1535276, 1647486, and 1738598), and is licensed under a
Creative Commons 4.0 Unported License. Based on a work at
www.BootstrapWorld.org. Permissions beyond the scope of this license may be available by contacting
schanzer@BootstrapWorld.org.