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\nIn new mathematics and statistics courses, ENG students will learn to analyze huge data sets and be introduced to machine learning, a major component of autonomous systems, like self-driving cars and robotics.<\/em><\/p>\n
For decades, product developers have depended on a primary engineering discipline to turn a design into a product. Car makers, for example, were helpless without the skills of mechanical engineers. But these days, those same car makers hire software engineers as well as computer, electrical, mechanical, and systems engineers. Why? Because today\u2019s products, at least those produced by innovative companies, require an interdisciplinary approach, one that often uses massive amounts of data.<\/p>\n
As the increasing importance of data science, not just in the design of cars, but in healthcare, urban design, the internet of things, and other fields, has changed the workplace for engineers, it has also changed undergraduate education at the College of Engineering. Beginning in the fall, all students will take courses in data science, and they will learn to apply relevant tools and techniques to some of today\u2019s cutting-edge, multidisciplinary technologies.<\/p>\n
\u201cThe era of the single-discipline engineer is over,\u201d says Kenneth R. Lutchen dean of ENG. \u201cMost innovation now requires multiple engineering disciplines interacting with large data sets. Making sure our students are literate in data analysis is in keeping with our mission to create societal engineers. With this knowledge, Boston University engineers will have the tools to improve society for many years to come.\u201d<\/p>\n
The curriculum change began in fall 2016, when an ENG task force was charged with recommending revisions to the undergraduate curriculum to ensure that graduates are better prepared to work in the emerging digital and maker economy.
\n\u201cWe are one of the first engineering schools nationally that has designed a curriculum for which students in every major will take an interdisciplinary, data-driven approach,\u201d Lutchen says. \u201cWe are aware that in the future, every engineering discipline, from mechanical to biomedical to computer, will intersect with data science.\u201d<\/p>\n
The new curriculum will replace ENG\u2019s existing two-credit linear algebra course with a three-credit computational linear algebra course. A single new four-credit probability, statistics, and data science for engineers course will replace the separate and distinct probability and statistics courses that had been offered by each department. The new course will include the tools and techniques to analyze huge data sets and an introduction to machine learning, which is becoming a large part of autonomous systems. Three 400-level elective courses\u2014introduction to machine learning, smart and connected systems, and introduction to robotics\u2014will also be offered and will be open to students in all majors.<\/p>\n
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Data sets can process data from in-home medical sensors or help to develop drug molecules targeting specific microbes.<\/em><\/p>\n<\/div>\n \u201cTypically, engineering students are not expected to have this data science foundation,\u201d says Thomas Little, ENG associate dean for educational initiatives and a professor of electrical and computer engineering. \u201cOur new curriculum introduces them to mathematical concepts that allow them to appreciate the analytical capabilities provided by contemporary large-scale computing.\u201d<\/p>\n Little says data analytics and data-driven technological systems are playing a central role in many rapidly emerging technologies, such as smart cities and self-driving vehicles. \u201cCyber-physical systems are producing and consuming massive amounts of data, and safety is often critical,\u201d he says. \u201cWe need to be sure our graduates are prepared to use these new analytical techniques to tackle these modern challenges.\u201d<\/p>\n In another, related curriculum change, all freshmen will design and build a product\u2014whether physical or software\u2014as part of the introduction to programming and introduction to engineering modules. Little says this will help build a stronger connection between the challenging first-year coursework and what students will do after graduation.<\/p>\n \u201cThis reflects what is going on in the maker world,\u201d he says. \u201cOur Engineering Product Innovation Center<\/a>\u00a0allows us to bring this to all students. This will transform the freshman year. Our students come to us wanting to build things, and we need to keep that alive.\u201d<\/p>\n The new curriculum will apply to all students in the next academic year. In addition to incoming freshmen, current students who have not yet taken linear algebra or probability and statistics will take the new courses that include data science.<\/p>\n \u201cStudents need this now,\u201d says Lutchen. \u201cThe next wave of innovations that address our societal challenges and life quality need a workforce comfortable in the era of big-data and interdisciplinarity.\u201d<\/p>\n