Bachelor of Arts in Data Science

Data science is the practice of collecting, organizing, analyzing, and communicating data to solve real-world problems. It combines statistics, programming, and domain expertise, since data alone isn't useful until someone knows how to ask the right questions, work with messy information, and translate findings into meaningful insights. At Redlands, the program emphasizes applying those skills within a field you care about, whether that's health, economics, environmental science, or the arts.

Data science sits at the intersection of all three, but the Redlands program has a distinctive angle.

Computer science focuses on building software systems and algorithms. Data science borrows those programming skills but uses code as a tool for analysis rather than an end in itself and no prior CS background is required to start. Economics and business analytics use data within specific domains, but often with less technical depth. The Redlands program is designed to pair with those fields, making graduates stronger analysts than either discipline produces alone. Applied math provides the theoretical foundations (statistics, linear algebra, probability) that data science draws on, but the Redlands program extends that grounding into real datasets, ethical reasoning, and career preparation.

The key difference: unlike standalone data science programs at large universities, Redlands intentionally pairs the major with a second field of study. The goal isn't to produce generic data scientists, it's to produce the data expert in biology, psychology, accounting, or whatever discipline a student loves.

In our first year running the capstone, students tackled three remarkably different real-world problems: analyzing customer feedback for fashion businesses using sentiment analysis, building real time object detection models to track user movement, and developing machine learning models to forecast tourist package and hotel pricing. The range reflects exactly what the program is designed to do, give students the technical tools to work on problems that matter to them.

For a brand new program, our early outcomes speak for themselves. Two of our three inaugural graduates were admitted to graduate programs: one to Washington University for Engineering, another to Pomona's Interdisciplinary Data Science program. A Data Science minor also completed faculty mentored research on predicting bank failure using time series gradient boosting algorithms and is heading to the Federal Reserve in Washington D.C.

Students also build their careers while still at Redlands. For example, internship opportunities with ESRI, on campus data roles in the business department and advancement office, and competitive local hackathons, where our students have taken home prizes. Faculty actively involve students in their own research, creating pathways into both industry and graduate study from day one.