In my mind, there have been three distinct types of classes throughout my BSIS: the ones that genuinely reshaped how I think about information and analytic coding; the ones I wish I had taken sooner — because by the time I finally got to them, I had already learned most of the content on my own to support other classes; and finally, the classes that didn’t contribute much to my understanding, or in some cases, actively hindered it.

I’ve talked a lot about those foundational classes — Data and Text Mining, Predictive Analytics, and Information Behaviors. These stuck with me the most and had the biggest impact on how I understand and approach information science. They introduced me to core theories, algorithms, and methodologies that continue to guide me in how I solve data problems today. Information Policy and Ethics was another one that stayed with me. While I don’t plan on going into policy, that course gave me a strong foundation in thinking through ethical considerations in research. I still refer back to those notes when I’m making decisions for a project. (One small thing I’ve never told anyone but always found hilarious: I look Information Policy and Ethics over Summer 2024, and spent that entire summer being drilled on the importance of asking why data is being used, where it’s coming from, and how to ethically engage with data mining… only to start Fall 2024 with, “Anyway, here’s how you data mine.” It absolutely cracked me up. 10/10 course progression.)

The classes I wish I had taken earlier include Data Visualization and R Programming. By the time I got to them, they were mostly review — helpful, but not new. On the flip side, classes like Database Concepts and Professional Writing didn’t do much for me, and in some ways felt like they actually slowed me down.

That said, those foundational courses are what sparked and solidified my interest in machine learning and predictive analytics. This degree program has done a great job of introducing me to the tools and core concepts of the field — and, more importantly, helping me figure out where and how to keep learning. If I had one major critique, it’s the lack of mathematical depth. I’ve talked to Dr. Hagen about this before, and she explained that the program is designed more for social scientists, and that most students won’t need the deeper mathematical understanding to succeed. I get that — but as someone planning to apply to PhD programs, I’ve found myself having to go back to learn the higher-level math I didn’t get in this degree. If I could give one piece of advice to future students in the data science track, it’s this: take calculus. Not because it’s required, but because it really is that important.

That ties into what I liked and didn’t like about the program. My biggest dislike is, unsurprisingly, the lack of mathematical rigor. I wish more classes dug into the why of the algorithms in a mathematical sense, not just the how from a programming perspective. Outside of that, though, I don’t have any major complaints. I’ve liked my professors, appreciated the flexibility of online classes, and enjoyed the core concepts we explored. I do wish I had more chances to meet and collaborate with classmates, but I’ve made my own way with that — joining Dr. Hagen’s lab and staying in touch with people I worked well with in group projects.

Right now, after a lot of conversations with Dr. Hagen, my parents, and a few other professors, I’m committed to applying to a PhD program. I’m going to spend this next year getting caught up on advanced math and prepping for the GRE, with plans to start applications in the fall. I’m still narrowing down which programs I want to apply to, but I know I’m looking for something focused on machine learning, data analytics, predictive modeling, and/or human-data interaction. I’m especially interested in how we know what we know in the current data age, how AI is shifting our understanding, how people learn from and respond to information, and how we build systems that reflect or reshape that. I don’t quite know what programs exactly I plan on applying to, but that’s my current plan for the summer and fall.