Northwestern University in Evanston, Illinois, entered the data science education field this semester with a full-time, 15-month master of science in analytics program offered at its McCormick School of Engineering and Applied Science. Interest in the program proved strong and attracted hundreds of applicants for only 30 slots, says Diego Klabjan, the program's director and an associate professor of industrial engineering and management sciences.
"The goal is to have a highly selective, high quality program so that's why we're not going for numbers," says Klabjan. "We don't want to have 60, 70, 80 or 100 students."
Ideal candidates hold a bachelor's degree in an analytics-related field, such as statistics, computer science, economics or industrial engineering, and have between two and five years of work experience in analytics, he says. Most of the 33 students in the first class meet these parameters, says Klabjan, adding that there are exceptions in the group such as recent college graduates and IT professionals with more than a decade of work experience.
The university went with a master's program because analytics is a professional method of science and an undergraduate degree delivers the required foundation, says Klabjan. Teaching the fundamentals, like basic data modeling or statistics, would require a program longer than 15 months, he adds.
The program is divided into thirds and teaches the IT, science and business aspects of analytics, says Klabjan. Some topics covered in the IT portion include data warehousing and workflow management. Science courses will look at machine learning and data mining, among other topics. The business curriculum includes communication, project leadership, which gets a full course, and conveying information to business users. Elective courses based on vertical industries like marketing and health care are also offered. Students will spend their summer completing a mandatory off-campus internship before returning to campus for the final quarter.
To learn the software behind big data, students attend a software boot camp a few days before the program starts during which they're trained in IBM's SPSS and Cognos, Tableau, Hadoop and SAS products.
Beyond the classroom learning, students will serve as de facto consultants and work on business-sponsored data projects. During the first quarter, students start an eight-month project and complete a capstone project in the final quarter. Students, divided into teams of four, will interact directly with participating companies during weekly meetings and be responsible for delivering a completed project.