Penn LPS Online Certificate in Data Analytics ‘20
Master of Education, Holy Family University ‘03
Master of Science, Psychology, ‘99
Bachelor of Arts, Psychology, La Salle University ‘97
“Data has always been part of my work,” says Susan Hassett, an enrollment systems analyst for the University of Pennsylvania’s College of Liberal and Professional Studies (LPS). Susan served in student advising roles at Penn for about a decade and especially enjoyed the process of translating student data into actionable insights. Her current role entails using data every day. Susan notes, “One of the most enjoyable parts of my job is working with data and presenting it in a meaningful way for different program directors and administrators.” Susan enrolled in the Penn LPS Online Certificate in Data Analytics to learn more efficient ways of processing data and to discover other tools she can use at work to yield additional data relevant to program design, marketing, admissions, advising practices, and strategic planning.
“The emphasis on learning R was a deciding factor in my decision to complete this program,” Susan recalls. R is a free programming language used primarily for data analysis; Susan notes it has a steep learning curve, but “it is robust with many applications once you learn.” For example, R allows users to “clean, organize, and analyze data with just a few lines of code, which is so much faster than what you can do in Excel,” Susan explains. “That alone is going to save me a lot of time in my job.”
As someone who works full time, Susan valued the convenience of taking courses online and not having to travel to be in a classroom. She also appreciated that the courses had synchronous and asynchronous elements: students watched video lectures independently on their own schedules and came together as a class with the instructor once a week to reinforce concepts and learn new content. “I had taken a non-credit data course outside of Penn in the past that was completely asynchronous, and I felt disconnected from the content and the instructor. In the certificate courses, there is a weekly touchpoint with the instructor, which was really helpful for me,” Susan reflects.
Susan describes the course content as “nicely presented and very thorough” in that the courses tie together and give students a good overview of a vast field. “I learned so much and still only dipped my toe into all the possibilities that R has to offer,” Susan remarks. She adds, “the courses equipped me to keep learning about these topics independently.” She notes that the instructors encourage students to familiarize themselves with the community of R users online. That way, students know how to tap this community’s knowledge to troubleshoot any questions they encounter after completing the certificate.
Susan says completing the certificate was “a lot of work, and there was a lot of new information to take in, but it didn’t feel overwhelming.” She attributes that to her instructors, who explained the material thoughtfully and methodically. Susan found the subject matter to be very different from everything she had learned about data before, which made her coursework feel like a refreshing change of pace from her day job rather than an extension of it. Additionally, Susan was surprised to discover that she enjoyed the coding aspect of the courses: “I never thought of myself as a computer programmer, but I found that I’m relatively good at coding!”
For her final project, Susan used R Shiny to create an interactive app that illustrates the correlation between zip code and school suspension rates amongst public school students in Philadelphia. “It contains a map of the city where you can click on each zip code and see the percentage of suspensions and the different types of infractions,” she says. The project continues Susan’s career-long interest in using data to understand the advising needs of different student populations. She is interested in creating a similar map-based visualization for her job at Penn. “The data certificate courses drove home for me that your analysis can only be as good as the data you have and the amount of data you have. But if you’re following the correct methods, your analysis can yield meaningful results,” Susan notes. “The courses definitely enhanced my skills and gave me a great foundation to build on. The world of R, so to speak, is very big, and I’m excited to explore it.”