Interview with Kevin M. Purcell, Associate Professor of Data Science and the Program Lead for Graduate Analytics at Harrisburg University

Kevin M. Purcell

The demand for skilled data scientists and managers with the capability to utilize big data to enhance their enterprises is developing quickly and there’s never been better or all the more energizing time to seek after a degree in this high-development field. We got an opportunity to speak to Kevin M. Purcell, Ph.D., Associate Professor of Data Science & Academic Program Lead for Graduate Analytics of Harrisburg University of Science and Technology. Kevin described how Harrisburg’s Analytics program provides real-world use cases and practical skills in order to make a noteworthy career in data analytics and big data.

 

What is the edge your Analytics and Data Science Program has over other institutes in the industry?

Harrisburg University and our program specifically has as a core tenet the goal of closing the gap that exists between a recent graduates’ capabilities and the capability required to be a true differentiator in the workforce.  The Analytics program at Harrisburg University does both through the design of our curriculum and through the development of our faculty.  The Analytics curriculum here at HU is based on an experiential model that has students immersed in real-world scenarios as quickly as possible, including scalable and dynamic data challenges. Our students are required to conduct original research as part of their degree requirements and our research minded culture encourages their involvement in collaborative projects with faculty.  Finally, our faculty themselves are recruited with an eye toward keeping our students connected with the needs and trends of the industry.  At Harrisburg University, two-thirds or our faculty are also professionally tied to many of the industries that are affected by data science analytics. The wealth of experience and perspective these individuals bring to the classroom is a true advantage the over 1200 students that seek a degree from Harrisburg University.

 

Kindly brief us about your role at the Institute/ University’s Analytics and Data Science Program and your journey in this highly promising sector.

At Harrisburg University, I am an Associate Professor of Data Science and the Program Lead for Graduate Analytics. I also hold the position of Chief Scientist at WildFig, a data science and analytics consultancy based in Harrisburg, PA.  My own journey, like many of the first generation of data scientists, has been rather unique.  I hold post-graduate degrees in the Biological and Environmental Science and have worked as an academic research and teacher for most of my early career.  My research program uses data-intensive methods to study disturbance in complex ecological and economic systems.  Three years ago, I moved off of the academic track to help found a startup focused on helping organizations negotiation the complicated path to becoming data-driven.  At that time, I began teaching at Harrisburg University during what can only be described as a period of explosive growth.  Following the exciting and popular launch of our doctoral program, I was tapped to help to lead the graduate analytics group.

 

How will this program be delivered/taught? Is there any industry participation in the course?

The Harrisburg University Analytics program is offered through an Executive program that caters to professionals with active careers.  We offer a hybrid in-person/online curriculum delivery model, that allows our students to pursue their academic development in parallel with their current professions.  Courses are taught synchronously with weekly online class sessions in the evening and several on-campus in-person meetings, a semester that occur on weekends.

 

What tools and techniques are covered as part of the course?

The HU Analytics program is grounded in the tools and techniques of the industry. We focus on programmatic approaches and avoid the ephemeral tools that come and quickly go in a technological field like data science. Perennial favorites of our program are programming languages like R and Python, as well as scalable technologies like TensorFlow and Hadoop. Our program does offer exposure to industry stalwarts like Tableau and SAS but more often than not we focus on open-source programmatic tools that are portable and represent the popular trends of the industry.

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