This fall, current and incoming Pitt students can begin pursuing a joint Data Science major between the Dietrich School and the School of Computing and Information. Sixty-one credits in courses across several departments will prepare students to enter the burgeoning field of data science with the necessary competencies drawn from statistics, mathematics, and computer and information science.
According to LinkedIn’s 2020 Emerging Jobs Report, data science saw a 37% annual job growth, and the field came in third for the top emerging jobs in the United States. Countless fields require professionals who can collect and leverage large data sets to make informed decisions and improve society, including information technology, financial services, and higher education.
Classes like Applied Discrete Mathematics and Data Structures will provide students with foundational knowledge of the four literacies this major addresses — data, algorithmic, mathematical, and statistical. Majors will then pursue expertise areas and specializations, such as data analytics and computer systems, and finish the curriculum with a capstone course.
Higher-level courses will expose students to real-world data sets in order to apply what they’re learning to tangible problems and solutions. That’s why both schools have worked to design the new Data Science Foundations course (STAT/CMPINF 1061) to include a lab component. These courses also encourage students to interact with other elements of data analysis and collection, including the ethical use of data.
Bruce Childers, Interim Dean of SCI, notes this is a great time to launch the new major with the Provost's recent announcement of the Year of Data and Society at Pitt for the academic year 2021-22, and the recent report from the Data Science Task Force.
“Data science needs training in all three domains,” says Satish Iyengar, statistics professor and department chair. “If you take one out, the table falls.”
Andrew Lotz, Dietrich School assistant dean and faculty member in the Department of Political Science, says those involved in planning the major wanted to make sure students could feasibly include it in their academic plans, such as doing a double major with one of the many other fields that would benefit from data acumen. In order for students to do this in a four-year timeframe, this major allows for certain courses to be cross-counted or counted multiple times for degree requirements.
But what especially excites Lotz about the new Data Science major is the opportunity for interdisciplinary collaboration. Students will learn the methodologies of several disciplines, and they’ll benefit from the joint efforts of faculty from throughout the University.
“It gives students a natural inroad to learn [several] disciplinary languages instead of one. These connections are there. Students are better [prepared] when they have all these connections,” Lotz says. “It enables faculty with that nudge to make things speak to each other.”