In the STEM _elds, a natural way to promote integrative learning is through exposure to real world problems that inherently require the convergence of skill sets across a broad range of _elds and expertise. Data challenges have proven to be an e_ective way to promote knowledge and discovery in the Big Data era and provide unique opportunities for team science. This proposal aims to promote formal integrative learning experiences through innovative course development around data challenges that target graduate students in the quantitative sciences. The pilot project will provide critical insights into how to modularize and generalize courses of this type. This proposal capitalizes on several existing strengths, including: (1) the popularity and necessity of data mining, (2) existing hybrid course infrastructure and materials, (3) a research interest group, and (4) highly quali_ed faculty. Our long-term vision is to modernize integrative learning in STEM _elds through data-driven integrative learning.