Data-Savvy Students

Imagine what we could do with the streams of data rushing from Fitbits, Nests, satellites, microscopy, smart buildings, mobile phones, auto dashboards, credit card purchases and just about every other source of information that’s captured, tracked and shared. Stacy Tantum wants every Duke engineer to be able to envision the possibilities—and to turn them into reality.

“With all this rich data, how can we interpret it to learn new things, see unexpected patterns and make better decisions?” she says. “These are skills we want all of our students to have.”

As the Bell-Rhodes Associate Professor of the Practice in the Pratt School of Engineering, Tantum is leading development of a creative new course designed to give every engineering undergraduate a foundation in the fast-growing field of data science. Piloting this fall, “Introduction to Data & Decision Sciences” will soon be a sophomore-year staple.

It’s part of a triad of new or revised courses set to debut over the next year that will transform the Duke Engineering undergraduate experience. Also including a first-year, team-based engineering design course and an applied computing course, the requirements will create “a signature undergraduate curriculum that gives all students project- and problem-based engineering experiences early in their studies,” according to Dean Ravi Bellamkonda.

With a focus on team-based, authentic problem-solving, the new data course builds on a highly successful summer program called “Data+.” The award-winning program led by the Information Initiative at Duke (iiD) brings small groups of undergraduates, graduate students and faculty together to design data-driven solutions to interdisciplinary challenges, most provided by external clients. (Read more about Duke Engineering students' experience in Data+)

The approach has proven enormously popular, and may even aid recruitment and retention of students underrepresented in the field, according to iiD director Robert Calderbank. “Data+ had over 300 applications for 70 spots in 2016—over half from women,” he says. “In a world where women are still pursuing STEM majors at lower rates than men, that is encouraging.”

Plus, team-based labs that challenge students to solve real-world, potentially messy challenges, combined with structured teaching, give the core concepts a kind of “stickiness” that by-the-book approaches just can’t match, says Tantum.

“We want our students to really dig into data science—to learn to define problems, determine what data they need to answer questions, explore and visualize the data using concepts from probability and statistics,” Tantum says.

“Our goal is for each student to emerge with an understanding of how to use data to inform and guide their work as engineers.”

“Comfort with data will be an integral skill for engineers of the future,” adds Bellamkonda. “We see Duke as the place that will lead the way.”

 Intro to Data & Decision Sciences

New course for all Duke Engineering sophomores
Piloting 2017-18 academic year

Format:

• 1 lecture, 2 labs each week
• Includes both structured exercises and real-world problems
• Student teams work on authentic problems from clients in industry, academia & beyond

Learning objectives:

• Defining the problem
• Experiment design (gathering data)
• Data visualization, exploration, and presentation
• Probability and statistics concepts
• Decision-making in the presence of uncertainty

End goal:

All students learn how to extract information from real-world data to derive insights, support informed decisions and guide their work as engineers