A Swift Approach to Learning Data Science

Look at what you made her do! At the University of Virginia’s School of Data Science, MSDS residential student and ambassador Caroline Kranefuss recently led a live coding demo titled “Accessing Taylor Swift Songs Using the Genius API.” The event was part of the School’s Coding Project Demo Series, designed to showcase how students in the master's program apply classroom concepts to real-world solutions.

“This was a course project I did in my data engineering class,” Kranefuss began. “It’s part of one of the modules we did on APIs (Application Programming Interfaces) which allow different software systems to talk to each other. In this case, we’re using Python to connect to Genius.com, a popular website for song lyrics.”

While her demo technically revolved around Taylor Swift’s discography, the real subject was empowerment — not just the kind Swift sings about, but the kind that comes from learning how to command data. Using pop lyrics as her muse, Kranefuss revealed how the art of programming can be approachable, creative, and even a little fun — proof that data science doesn’t have to be a “Cruel Summer” of complex code.

Throughout her walkthrough, Kranefuss emphasized that good data science is less about perfection and more about curiosity. “I like to comment my code,” she said early on. “It is a really good practice so that when I go back, I know what I did. When other people look at my code, they understand what’s going on.” That simple tip doubled as a larger philosophy: clarity, collaboration, and reproducibility are the heart of data work.

She also offered a clever reminder about security, the programming equivalent of guarding your "Blank Space." When connecting to APIs, Kranefuss explained, students should never paste private credentials directly into their scripts. Instead, she demonstrated how to store access tokens in hidden “.env” files. “If I do it this way,” she said, “I can post my code online, and no one can see my passwords. They can run the same code with their own credentials.” Kranefuss emphasized that coding responsibly makes your work safer and shareable.

What struck attendees most was how naturally she blended technical rigor with approachability. Using the Genius API as her data source, Kranefuss showed that every dataset, even a pop star’s lyrics, can be a playground for learning. As she described how to convert a massive .json file into a neat, readable table, she turned what could have been a tangled mess of code into a story about finding structure in chaos. “Data scientists spend about 90% of their time cleaning and organizing data,” she said. “This class really showed how valuable that process is.”

Beyond the demo, Kranefuss spoke about how the UVA MSDS experience prepared her for this technical work. She credited Quantitative Foundation associate professor of data science Jonathan Kropko’s data engineering course with teaching her the patience to debug thoughtfully and the joy of learning collaboratively. 

That sense of community is, in Kranefuss’s words, what makes the program feel like a homecoming. Students come from all kinds of backgrounds, from fine arts and English to computer science and industry, and the program is designed to meet them where they are. “You’re totally good,” she reassured one attendee who asked about coding experience. “This is what you’ll be learning.”

For prospective students nervous about keeping up, Kranefuss offered a few timeless tips: practice consistently, take advantage of UVA’s preparatory boot camps, and don’t be afraid to ask for help. “There’s no shortage of knowledge out there,” she said. “And there’s no one right way to learn. It’s all about what makes you feel confident coming in.”

By the end of the session, what began as a technical demo about APIs had transformed into something more personal: a story about learning to speak the language of data without losing your voice. “It’s a little advanced,” Kranefuss admitted with a laugh, “but I wanted to show what’s possible, that by the end of your first semester, you’ll be able to do things like this.” Caroline Kranefuss made one thing clear: Data science, like good songwriting, is all about connecting the dots. Whether you’re a Swiftie or a statistician, sometimes, you just have to “Shake it Off” and keep coding.