2024 Data Hack Competition

Data Hack is a class where students learn about data cleaning, visualization, and descriptive analysis using R programming language. Throughout the quarter, the students learn the whole process of obtaining raw data and making it ready for analysis, therefore covering a wide variety of topics such as web scraping, merging and reshaping datasets, and even coding with AI.

At the end of the quarter, the students have the opportunity to show the skills they learned in a competition for cash prizes. They are randomized into small groups, where they have the freedom to choose a public policy issue in California, describe it, and present the evidence in front of a panel of external judges. This year's winners covered the following topics: Rehabilitation’s Effectiveness, Housing Unaffordability, and Educational Inequality.

This year's winners were:

1st Prize: Quyen Le, Bravo Choi, Evan Gao, Akshat Rohatgi, Emily Tashiro, Song Zhao

Topic: Educational Inequality in California

2nd Prize: Siduo Zhang, Enno Klotz, Katya Rodova, Katherine Nesbitt, Alexander Patton, Kylee Murray

Topic: Housing Unaffordability Crisis in California

3rd Prize: Ben Baak, Lucian Mahan, Shreya Sinha, Sammy Bono, Johnathan To

Topic: The California Department of Rehabilitation’s Effectiveness

We want to thank Camilo Abate and Michael Topper for teaching this class.

We also want to thank our fabulous judges: Javier Birchenall, David Silva (Buellton City Council), and Anna Jaskiewicz!