Computational Data Science at Penn State University

The Pennsylvania State University offers undergraduate students a few different options to earn a degree in Data Science. There are three options provided by the school: Applied Data Science @ College of IST, Computational Data Science @ College of Engineering, and Statistical Modeling Data Science @ College of Science.

I graduated in Fall 2021 with a B.S in Computational Data Science and here are a few observations I made about this program specifically. The first observation I made is that the curriculum is very intensive in Statistics and Mathematics. Almost every semester of undergrad I had taken a math class and/or a statistics class (to the point where I earned a math minor unknowingly). I believe that all Data Science options start with the same basic math classes like Calculus I/II/III, linear algebra, etc., however as I reached my 3rd year at university I was taking much more theoretical classes like numerical analysis, probability theory, and similar classes. The second observation I made is that there is a very heavy emphasis on the computational portion of the degree. Up until the end of my second year my classes aligned with the computer science degree path with many shared classes like DS&A, discrete math, & OOP. There is a very heavy focus on the computational foundations of the data sciences, including the design, implementation and analysis of software that manages large distributed data, as well as best practices when developing software.

I enjoyed the flexible curriculum provided for this major because it really caters to your interests in the data science field. For example some elective classes that I took include: computer vision, AI, machine learning, and privacy and security. I also believe that the classes provided are very practical and applicable for data engineering roles after graduation. For example, CS 410: Programming Models for Big Data, introduces students to Hadoop, MapReduce, Spark, Scala, parallel programming, and similar topics- where almost all topics are standard industry practices. Unless the undergraduate student had an internship working with very large datasets, these classes are a main exposure point to handling large datasets and working with clusters.

Overall, I enjoyed my time as a computational data science student at Penn State, and I felt that the curriculum did a decent job in providing the fundamental material I needed to succeed in my job post-grad.