Introducing the Applied Data-Driven Methods Graduate Certificate Program

As data generation increases exponentially in all facets of life — from health care to social media — the workforce faces a shortage of data professionals who can leverage that data to make decisions and predict outcomes. Mirroring this demand, Indeed ranked data scientists as the eighth best job on its 2020 list, citing a 77.57% growth in the number of job postings from 2016-19.

Pitt’s School of Computing and Information has developed the Applied Data-Driven Methods (ADDM) Graduate Certificate Program to ensure enough graduates with a data-oriented skill set enter the workforce. Designed for post-baccalaureate students whose academic background lies outside of computing and information, the 12-credit ADDM certificate will provide students with a deeper understanding of skills like programming, machine learning, data cleanup, and more.

Adam Lee, Professor of Computer Science and SCI Associate Dean for Academic Programs, says the ADDM Certificate aims to address key computing-oriented competencies required of effective data scientists as outlined by the National Academies of Science, Engineering, and Medicine.

“It’s about more than just the computing,” Lee says. “It’s about understanding the data you’re processing and making decisions based on it and being able to justify those decisions.”

The program begins with Introduction to Data-Centric Computation (CMPINF 2100), which Teaching Assistant Professor Joseph Yurko piloted in the fall 2020 term. There, students learn computational foundations such as data structures, algorithmic thinking, and programming. Students will utilize these skills throughout the remaining core and elective courses while they acquire other competencies such as data management and curation and data modeling and assessment.

ADDM was designed with three objectives in mind, including an effort to compliment the Master of Library and Information Science degree program with data-driven instruction. Students in this program, many of whom come from a social science or humanities background, would apply this skill set to tasks throughout the information professions, such as navigating electronic collections and analyzing community data to make informed decisions.

“This is another way to diversify that skill set and enabling them to, in a very competent manner, make sense of large data sets and learn from them,” Lee says. “If you can navigate that data and help people you work with understand that data, that’s certainly a good thing.”

The design team also wanted the program to be accessible as part of stackable master’s degree programs at Pitt, wherein a student can combine several certificates from programs across the University to complete a master’s degree. This adaptability of ADDM reflects the multidisciplinary nature of data science programs, which necessarily combine computing and information competencies with a variety of other domain skills.

ADDM could also interest those looking to pivot their career by developing a greater data-oriented skill set without enrolling in a more intensive program, such as a 30+ credit master’s degree. Lee says any interested candidate can find a way to utilize this data training to better serve their field, from health professionals assessing patient outcomes to educators analyzing engagement with online learning platforms.

“Broader sectors of the economy are relying on people who can make sense of data and make decisions based on data,” Lee says. “It’s kind of hard to get away from.”