NYU has launched an undergraduate major in data science—a degree that will train students to deploy a cutting-edge computational approach in understanding and addressing a range of phenomena.
What is data science?
“Data science is a subset of statistics, which is about trying to capture all the relevant information in as unbiased and representative a way as possible,” says Wesley Chan, director of NYU’s data science program. “In that sense, it’s similar to what we do as statisticians, but in this case, we’re doing it at a much larger scale.” Though the data science approach is focused on data sets that are massive in size, almost impossible to extract into a form that’s useful for analysis by traditional means, Chan describes it as a subset of statistics.
The NYU Data Science Program
I recently spoke with the leader of this program, Professor Joseph DeRisi. We asked him about NYU’s commitment to data science and its approach to its first-year cohort. What is data science, and how is it different from statistics? People generally think of data science as a new degree or a subfield of a more established discipline. But at its core, data science is all about using data and statistics to understand the world. The practice of data science has been around a long time, but not with the kind of compute intensity that is used in modern analytics. Many of the practitioners are data scientists first, and they often find themselves thinking about research and development issues. What are the common uses of data science? Data science tends to be deployed in a variety of areas.
The Data Science Major
NYU has been developing courses in data science since 2007. In 2017, the university started the Data Science Undergraduate Major program. Based in New York, it will enroll 200 undergraduate students this fall. After years of training students in computer science, data science provides a more holistic approach. “It is a full-spectrum, quantitative approach to thinking about data, to data visualization and to both quantitative and qualitative analysis,” says Sara E. Lautman, associate dean and director of graduate programs in NYU’s Tandon School of Engineering. Students in the program will learn advanced data-driven skills and develop analytical and computer science expertise with an emphasis on large-scale data analytics.
Data Science Courses
NYU will offer a comprehensive curriculum in data science, including coursework that combines statistics, computer science, applied mathematics, and data visualization, in which students will learn how to exploit scientific research to solve practical problems, as well as classes that promote entrepreneurial skills to address global problems. Applications are now being accepted for the first set of data science courses at NYU. The first-year courses will combine the fields of statistics and computer science, with the option to choose one of three unique concentrations: statistics for data visualization, systems biology and computational biology, and data visualization applied to risk and behavioral decision sciences.
Data science is one of the top emerging fields in today’s technology-driven world. As such, the demand for talent in the field continues to rise as organizations look to make use of the massive amounts of data they are generating from various applications. There has also been a major shift in the approach towards the application of data science, which involves a combination of machine learning (ML) and statistics. Given the complexity of these professions, it is vital for individuals to have a thorough understanding of the field to have a leading edge when they go out looking for work.