Patrick Asztabski finds a home in the new data science major

Patrick Asztabski

Patrick Asztabski, a sophomore, recently transferred into the new data science program. He was previously an applied statistics major.

Q: What prompted you to switch majors?

A: I’ve always liked working with statistics and data in general. Statistics is a really valuable discipline for solving some real-life problems. Recently I took a computer science course because I’ve been curious to work with data science and computer programming. When I received an announcement about the creation of the major, I thought, “Wow, this is perfect!” This is what I wanted to do when I chose applied statistics as a major. I wanted to go into data science, but the major didn’t exist then.

Q: Have you chosen a concentration?

A: I have a few in mind, statistics or social technology studies. I’ve also thought about health data science.

Q: What does your semester look like, now that you’ve switched to data science?

A: While I was still an applied statistics major, I took STAT 381 Applied Statistical Methods and liked learning the different distribution methods. I like the challenge of translating a problem from English to math and back to English. I really enjoy the specificity of each problem. I also took MCS 260, where I learned Python.

This semester, now that I’m in the data science program, I’m taking four courses toward my major: CS 141 Program Design II and CS 151 Mathematical Foundations of Computing, where I’ll learn Java and C++; MATH 310 Applied Linear Algebra; and STAT 382 Statistical Methods and Computing.

This interview was edited for clarity.

UIC’s data science degree program officially launches this fall, but students can begin to take courses in the new major, which is housed in the computer science department. In addition to core courses in areas including foundational mathematics, statistics, computer science, and ethics, nine areas of concentration allow students to focus on a variety of industries that are increasingly dependent on data analysis. Learn more here.