Capstone Research Project

The Master’s curriculum culminates with a capstone research experience aimed at making theory applicable to life. Students are paired with external partners looking to receive practical insights into their data. To support the MS cohort throughout their research, the QTM department assigns a capstone adviser and solicits projects and data from community sponsors, carefully matching students with organizations that may be relevant to their specific interests. This also provides students opportunities to connect with project partners who often engage with the program as potential employers of MS QTM graduates.

QTM's approach to the capstone experience differs from most data science programs that would use a purely predictive model for a project that forecasts student success in high school. The result of that exercise might reveal that one of the best indicators of student achievement is private school attendance. The predictive model works well, but it does not tell us why students have success, and as a result, would be unhelpful for policy recommendations. QTM students, on the other hand, would decide to bridge this gap by uncovering the "why" — it might be the quality of education, the resources available at these institutions, or simply that parents who expect high achievement enroll their children in private school. A QTM capstone project incorporates predictive and causal analysis to tease out which notions are supported, and thus, the best course of action. The research possibilities are vast, and students will use real-world data to answer real-world questions. This integrated approach makes students essential in today’s data-driven market across several fields.