What? A $15K Data Science MS Degree from the University of Pittsburgh?

In December 2023, we covered new online computer science master’s degrees from Dartmouth College and the University of California at Berkeley. Designed for working adults with STEM backgrounds, these two groundbreaking degrees are both priced below $45,000, which is about a third of what Dartmouth charges for the on-campus version of its master’s program.

We also pointed out how those two announcements emerged just before a “disruptive” (sub-$30,000) pricing reset for online master’s degrees turned into a hot discussion topic during edX’s 2023 Global Forum in October 2023. That discussion was prophetic, and now we’re witnessing announcements of new programs that confirm some of the reported speculation during that conference session.

One of the first such announcements came from the University of Pittsburgh. Pitt has decided to price a new master’s degree program at only half of that disruptive price point: $15,000. Pitt calls their degree the master of data science, or MDS, and started offering the program online through Coursera in February 2024.

Few Americans had ever heard of this new occupation before 2012. That’s when researchers Thomas H. Davenport and DJ Patil published their famous Harvard Business Review article entitled “Data Scientist: The Sexiest Job of the 21st Century.” The article won widespread coverage from major outlets including the New York Times and the Boston Globe.

Based on an informal survey of only 35 data scientists at a time when no formal training in the field existed, their article defined the data scientist role as “a high-ranking professional with the training and curiosity to make discoveries in the world of big data.” Back when companies were just beginning to look for revenue opportunities within huge volumes of data in social media clickstreams containing images, speech, and video, most data scientists “had PhDs in some scientific field, were exceptional at math, and knew how to code.”

Davenport and Patil cite the invention of LinkedIn’s “People You May Know” feature in 2006 as an early data science triumph. That’s because the wildly successful addition of that single function boosted the platform’s clickthrough rate by a whopping 30 percent, generating millions of additional page views.

Davenport and Patil published a follow-up HBR article in 2022 under the title “Is Data Scientist Still the Sexiest Job of the 21st Century?” Although their earlier article presents interesting anecdotes, their later article’s analysis is more useful to those interested in data science degrees and careers.

For example, their 2022 update portrays data scientists as those who “combine programming, analytics, and experimentation skills” as “the key focus of the job continues to shift towards predictive modeling and the ability to translate business issues and requirements into models.” Along with this shift, the authors say that PhD degrees and programming skills have become less important as today’s companies “need to create and oversee diverse data science teams rather than searching for data scientist unicorns.”

They say that another change since 2012 is that data science has become better institutionalized. Today banks, insurance companies, retailers, healthcare systems, and even government agencies employ large data science groups, and Wall Street financial services firms may employ hundreds of data scientists. The authors continue:

A decade later, the job is more in demand than ever with employers and recruiters. AI is increasingly popular in business, and companies of all sizes and locations feel they need data scientists to develop AI models. By 2019, postings for data scientists on Indeed had risen by 256 percent, and the U.S. Bureau of Labor Statistics predicts data science will see more growth than almost any other field between now and 2029. The sought-after job is generally paid quite well; the median salary for an experienced data scientist in California is approaching $200,000.

Our recent research mostly confirms what Davenport and Patil say about the labor market. Hot demand exists for data science professionals, and their salaries are lucrative. According to U.S. News and World Report and the Bureau of Labor Statistics, across the nation there is currently an annual shortage of 59,400 unfilled jobs in this field. What’s more, the national median annual salary for data scientists was $103,500 in 2022, with the top 25 percent earning above $136,600. Plus the employment of data scientists is projected to grow 35 percent during the decade between 2022 and 2032—much faster than the average for all occupations.

Davenport and Patil are also roughly correct about demand and salaries in California, wher, according to the latest U.S. News data the median annual salary for non-management data scientists hovers around $150,000, and Silicon Valley’s data scientists in San Jose earn a stratospheric $233,320. California is also home to artificial intelligence firms like OpenAI, and recently, the short-lived firing of that firm’s CEO Sam Altman kicked off a bidding war by nearby Bay Area firms like Salesforce and NVIDIA for potential defectors among the company’s hundreds of data science professionals.

Hundreds of university data science programs now exist to meet this tremendous demand for data science professionals, and many award master’s degrees like Pitt’s. However, Davenport and Patil caution that these diverse curricula are not standardized, and in some cases they are not even complete relative to the requirements of some employers:

It’s unlikely that any single program can inculcate all of the skills necessary to conceive, build, and deploy effective and ethical data science analysis, experiments, and models. Indeed, making sense of the diverse educational choices even at a single institution is a challenge for prospective data scientists and for the companies that wish to employ them.

In particular, the University of Pittsburgh’s new program presents several innovative and remarkable features. For one thing, Pitt has decided to throw this master’s program wide open to potential students without a data science-related bachelor’s degree, including those with no prior STEM or computer programming experience.

They do that by applying a cutting-edge admissions paradigm called performance-based admissions or PBA, which we explain at length in our April 2024 feature article, “Performance-Based Admissions: Online Ed’s Most Disruptive Trend in Decades.” As part of a growing trend towards accessibility in the admissions process, Pitt is one of five universities on Coursera that added performance-based admissions during 2023.

In short, Pitt’s implementation of performance admissions means that its MDS degree program will accept any applicant who holds any bachelor’s degree in any discipline from any accredited U.S. university or any equivalent international institution—so long as that potential student earns at least a B grade of 80 percent in a single, three-credit-hour gateway course. Once the student passes that course with a sufficient grade, Pitt automatically accepts them into the MDS program, and their three PBA credits will count towards their graduation following nine more three-credit courses.

In other words, Pitt doesn’t require letters of recommendation, admissions tests, undergraduate or graduate course transcripts, application essays, or prerequisite courses. The PBA paradigm removes all these obstacles in favor of evaluating a sample of actual graduate coursework, making the program accessible to all college alumni. Along with earning a sufficient grade in the gateway course, potential students simply need to verify their bachelor’s degree for Pitt’s Office of Admissions.

Dr. Bruce Childers, the dean of Pitt’s School of Computing and Information (SCI), shared the following remarks about the program’s accessibility objectives in a prepared statement:

Our MDS removes entry barriers, reassesses admission processes, and harnesses technology to deliver an exceptionally accessible program that embodies Pitt’s high-quality, internationally recognized education. SCI is embarking on this new online degree program because we realize the importance of providing access to data skills and knowledge inclusive of all learners.

Students without a STEM background can begin with an optional series of noncredit courses if they’d like to build that foundation. The self-paced data science curriculum kicks off with coverage of core math, computer science, and statistics concepts.

Coursework then teaches practical skills such as programming in Python and R, designing and querying databases using SQL, and accessing and working with large real-world data sets in order to answer research questions and test hypotheses. The program then teaches students how to apply artificial intelligence, machine learning, and predictive modeling techniques.

Along with their coursework, students will build a portfolio of data science projects they can present to future employers. The program concludes with a capstone project that will enable students to further showcase their new skills.

Like most online degree programs, this one targets working adults. Pitt says it designed coursework in the MDS program to provide this group with schedule flexibility, while also incorporating “optional live sessions where students can interact with faculty and course staff throughout the curriculum.”

As discussed by SCI faculty and administrators during this January 2024 YouTube webinar, the school will give online MDS students access to the same types of resources as its residential students on campus in Pittsburgh. These resources include “student services, career resources, peer communications, and the same faculty.”

Although Pitt’s MDS degree offers several disruptive new innovations in admissions and pricing that are sure to give the program competitive advantages, it is by no means the only master’s degree in data science. A quick trip to Google will verify that most of the major players in U.S. graduate education have introduced data science degree programs within the past few years. However, not all of those offerings are flexible online programs geared to the needs of working adults.

Pitt may have patterned its new MDS program in some respects after an online master of science in data science originally launched by the University of Colorado at Boulder in 2021 and also available through Coursera’s platform. As we pointed out in a 2019 article here on OnlineEducation.com, CU Boulder’s College of Engineering and Applied Science gained a pioneering track record of experience by offering an online master’s degree program in electrical engineering starting that year. Moreover, a compelling selling point of that program also involved performance-based admissions.

According to a video presentation during the company’s March 2023 Investor Day, Coursera cited the performance-based admissions pathway as a major factor in the enrollment growth of Colorado’s data science master’s program. However, Coursera also asked the college for two program modifications that further drove up enrollment. The first modification requested a price cut that reduced total tuition to only $15,750, and the second asked the university to approve a dual-credential partnership with IBM. Under this arrangement, students who satisfy all the requirements for an IBM data science professional certificate also earn one graduate credit toward their master’s degree in data science from CU Boulder.

Colorado accepted both of Coursera’s requests and as a result, the changes drove impressive enrollment growth during spring 2023. The program posted a 50 percent annual increase in spring 2023 recruitment, along with a 70 percent increase in new student conversions over the prior year’s levels. Look for IBM and the University of Pittsburgh to announce a similar dual-credential partnership during the next few months.