Distinctly Berkeley Data Science Major Has Wide Appeal

With 780 students filing pre-declarations as soon as they became available earlier this fall, UC Berkeley’s new Data Science major is on the way to quickly becoming one of the most popular on campus.

Designed through collaboration across diverse disciplines, the Bachelor of Arts in Data Science in the College of Letters and Science was developed in response to intense student, faculty, and industry demand for graduates equipped to propel knowledge to action in a world transformed by the digitization of everything from DNA to political speeches to radio signals from distant galaxies.

“We are thrilled to introduce our new Data Science major, which will produce graduates who not only have deep technical expertise, but who also know how to responsibly collect and manage data, and use it to inform decisions and advance innovation to benefit the rapidly evolving world they’re graduating into,” said David Culler, Interim Dean of the Division of Data Sciences.

Senior Eleanor Fleming, who plans to graduate this spring as a Data Science major, likes the versatility of the degree. “I feel like if you have the tools to analyze data, a strong understanding of the foundations of data science, it gives you the opportunity to explore a lot of things. It makes you valuable in whichever industry you end up in.” She’s currently part of a team working to design an autonomous drone; when she graduates, she’ll be applying her skills at an asset management firm.

If you have the tools to analyze data, a strong understanding of the foundations of data science, it gives you the opportunity to explore a lot of things.

Junior and intended major Zander Ladd pictures using his knowledge to map and better understand the brain. “That’s my goal. I want to uncover this mystery that is the brain through statistical analysis.”

The major, which includes a requirement for a “domain emphasis” or specialization in a particular subject of interest, will enable students to apply the computational and statistical skills they acquire to pursue passions in a range of disciplines—in Zander’s case, Neuroscience.

“It really is something that’s open to the whole campus,” said Zander, a peer advisor for the Division of Data Sciences. “If you look at the domain emphases, you have Inequalities in Society, you have Ecology and the Environment, you have Human and Population Health…”

While the new degree has strong computational foundations, he said, “It’s not just computer scientists who jump into data science.”

The booming field of data science integrates aspects of computer science and statistics to analyze and draw inferences from data to produce knowledge in the context of a particular discipline or problem—for example, to illuminate the interplay of traffic patterns and air pollution. LinkedIn’sAugust Workforce Report 2018(link is external) highlights a significant gap between data science job listings and people with the skills to fill them, particularly in areas like San Francisco, Los Angeles, and New York, noting: “Demand for data scientists is off the charts.”

Depth, Breadth, and Context

The new major has a distinctly Berkeley character, with a focus on three dimensions:

• computational, statistical and mathematical depth, including core data science courses designed from the ground up;
• breadth, as reflected in the requirement for a “domain emphasis,” or specialization in one of an array of subject areas, including Evolution and Biodiversity, Inequalities and Society, and Organizations and the Economy; and
• societal awareness, or an understanding of the social and human contexts in which data are applied, and of related concerns such as privacy, governance, and the human impacts of a data-abundant society. 

Majors take foundational courses that emphasize programming, applying statistical methods to datasets, and analyzing and visualizing results, along with courses that open up the human, social, and ethical contexts in which data analytics are applied. Upper-level courses delve further into topics like probability and machine learning. Through the domain emphases, majors have the opportunity to explore courses from all across campus through the lens of data science, enabling students to integrate their technical knowledge into new discoveries. Throughout, opportunities like the Discovery Program and Data Collaboratives offer students the chance to apply their knowledge to advance research and social impact.

“This is an exciting moment, said Cathryn Carson, Professor of History, who has co-chaired the data science curriculum design team and been the faculty lead in the undergraduate program for the past two years. “With engaged support across campus, we’ve been able to build a strong, integrative major for our students.”

The structure of the major will support double majoring, with the domain emphases requirements often overlapping with upper division electives in other degree programs. In the coming year, the Division of Data Sciences also anticipates releasing a minor in Data Science, which will give an ever-larger group of students the opportunity to build data science skills.

Data Science Education Buzzing at Berkeley

The major is the most recent addition to Berkeley’s thriving Data Sciences educational program, which continues to experience surging demand. This fall, for instance, more than 400 students are enrolled in courses that explore aspects of data science ethics, and almost 800 students are taking Data 100, the bridge to upper level data science courses.

Data 8, Berkeley’s entry-level class on the Foundations of Data Science, saw an enrollment of 1,300, half of them women, representing almost all majors. Reflecting the Division’s mission to empower students throughout campus to engage capably with data, Data 8 is accessible to all students—no advanced math or computing skills are required, and the class uses the Jupyter cloud computing infrastructure to prevent students from getting bogged down loading and launching new computer programs.

Vinitra Swamy, who worked in several capacities in the data science program before graduating last spring with a Master’s in Computer Science, said the variety of students she encountered in data science classes was one of the biggest draws. 

“As a student, the thing that was gratifying for me was that I would be sitting next to an Econ major and an English major, and their ways of viewing the same problems that I was viewing were so interesting and different from the way that I thought.”

Students like Vinitra, who eventually taught Data 8, have been key in catalyzing the major and powering the robust data science program, enabling it to scale quickly to meet student demand. In any given semester, hundreds of students are engaged in helping to develop courses and curricula, participating in research, and serving as mentors, tutors, and lab assistants in the hands-on Data 8 labs that allow students to learn in smaller groups.

Programs like Data Scholars encourage the involvement of students from groups that may otherwise be unfamiliar with or daunted by data science by providing peer support and research opportunities. Data Scholar Ollie Downs, an Integrative Biology major, said data science was never on their radar until they had a chance conversation with a student they met on the bus, who exhorted them to try Data 8. They enrolled, got hooked, and have been deeply involved ever since, finding ways to integrate data science into their biology program, and helping to coordinate the Data Science Peer Advising program.

A lot of people think of data science and they think of a very specific kind of person, and we’re showing that that isn’t necessarily true.

 “We have three women running the advising team, and our staff includes a lot of different kinds of people,” they said. “I think that’s really important because a lot of people think of data science and they think of a very specific kind of person, and we’re showing that that isn’t necessarily true.”

Knowledge to Action

The launch of the Data Science major comes on the heels of a new Data Collaboratives program, one of many research opportunities available to data science students. The Collaboratives link students with government, community, and business partners to leverage data to help address important societal challenges, from access to safe drinking water to disaster recovery to affordable housing. The Data Collaboratives build on existing programs for undergraduates to create and apply insights using data, such as the Modules and Discovery programs.

Modules are collaborations between faculty and the Division of Data Sciences that give students in classes in a wide range of disciplines the chance to work hands-on with data deeply related to their interests. Dozens of courses across UC Berkeley have incorporated data science Modules into their curricula, investigating immigration enforcement, environmental justice, and word use in political speeches, among other topics.

The Discovery Program provides student teams with the opportunity to participate in cutting-edge data research while engaging with community impact groups, government, business, and University researchers to address issues such as providing access to safe and affordable water, reaching affirmative action goals, understanding evolutionary patterns, and better coordinating disaster relief donations.

The Division of Data Sciences is continuing to evolve its structure, deepen its offerings, and create more outlets for students to grow.  The collective enthusiasm and unique collaboration of students, faculty, and staff involved promises a future of data science like no other.