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New machine learning and data science option offers ECE undergrads in-demand skills

Written By: Jason Daley

In the last couple of decades, technology has become very efficient at collecting information from the physical world, including wearable medical sensors, radar systems integrated into automobiles and satellites monitoring earth’s climate—as well as from humans by monitoring the decisions they make. But that massive trove of data is mostly useless on its own; sophisticated computer algorithms are needed to find patterns, extract meaning and make predictions from the data.

That’s why the University of Wisconsin-Madison Department of Electrical and Computer Engineering launched the machine learning and data science option for both undergraduate electrical engineering and computer engineering majors.

The option requires 18 elective credits in the 120-hour bachelor’s degree consisting of courses focusing on machine learning and data science in engineering. Courses in the option cover coding for data manipulation, analysis, and visualization, and machine learning topics from applied linear algebra and probability through artificial neural networks and deep learning. When students graduate, the option is noted on their transcript, giving them a valuable credential in future employment searches.

“The creation of a new option for our BS electrical engineering and BS computer engineering degree programs was encouraged by our industrial advisory board members,” says Susan Hagness, department chair and Philip Dunham Reed Professor. “They recognized the importance of providing our students with formal recognition of concentrated coursework in machine learning, signal processing and other data science and engineering topics that are so central to electrical and computer engineering, and so highly valued in industry.”

Assistant Teaching Professor Matt Malloy, who leads several of the courses in the option, says the demand for students with these skills is already huge. “Employers want students with this formal engineering background,” he says. “They also want people with the ability to analyze large amounts of data. The rigorous engineering coursework students do in ECE in addition to the data science coursework sets this option apart. It’s not something that you would get from another part of the university.”

So far, Malloy says the option is proving popular, with enrollment for its core courses doubling during its inaugural semester. Even more enticing, Malloy says students can augment the option with the accelerated master of science in machine learning and signal processing, a course-based program that takes only 12 to 16 months to complete beyond the bachelor’s degree.

The need for graduates with these types of skills is only likely to grow as researchers develop new and more powerful algorithms that will allow major advances in an almost endless number of fields. “This specialization within ECE prepares our graduates to solve the most challenging data science and engineering questions in industry across healthcare, communications, automation, robotics and more,” says Hagness.