The information is vast, the challenges daunting, and the tools statistical. But in the end, Harvard’s new class on big data is as much about people as it is about methodology, the Harvard Gazette reports.

The 29 students in “Statistics 183, Learning from Big Data,” work in teams that shift every few weeks, tackling challenges that involve enormous data sets. The students brainstorm and learn from their team members, but they also learn from the work of other teams. Each team posts its solutions to the class projects weekly, and the top three give overviews of their strategies. Students also lecture, presenting a different statistical method to the class each week.

“The learning curve is very steep, but it’s also very exciting,” said Sherrie Wang, a senior biomedical engineering concentrator. “No other class I’ve taken is graded this way and is so project-intensive.”

The course meets twice a week in Quincy House’s newly renovated Stone Hall, under the watchful eye of Assistant Professor of Statistics Luke Bornn and teaching fellow Alex Franks. Bornn said he designed the course to eschew the typical lecture-and-exam format for one that is project-based and emphasizes peer learning. In other words, the class, which is being offered for the first time this semester, is unlike any that Bornn himself has taken.

“This course flips on its head anything that I experienced as a student, intentionally,” Bornn said. “It’s very much all about what they can learn from each other.”

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