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Institute for Data, Systems, and Society to launch new MicroMasters and PhD programs

"The Alchemist" by Jaume Plensa sits on the campus of MIT

Interdisciplinary doctoral program in statistics and online MicroMasters program in statistics and data science begin this fall.


Press Contact

Scott Murray
Email: srmurray@mit.edu
Phone: 617-324-4563
Institute for Data, Systems, and Society

The MIT Statistics and Data Science Center (SDSC), a part of the Institute for Data, Systems, and Society (IDSS), announced two new academic programs today: the MicroMasters program in Statistics and Data Science, and the Interdisciplinary Doctoral Program in Statistics, both beginning in the fall.

The MicroMasters program, currently under development by MIT faculty, will be offered online through edX. “Digital technologies are enabling us to bring MIT’s data science curriculum to learners around the world regardless of their location or socioeconomic status,” says Vice President for Open Learning Sanjay Sarma.

The curriculum includes foundational knowledge of data science methods and tools, a deep dive into probability and statistics, and opportunities to learn, implement, and experiment with data analysis techniques and machine learning algorithms.

“The demand for data scientists is growing rapidly,” says Dean for Digital Learning Krishna Rajagopal. “This new program increases the supply of professionals who are on top of the data science of today, and who have the foundational understanding needed to keep on top of the data science of tomorrow.”

“The MicroMasters program precisely addresses the unmet educational demand of working professionals who are trying to train themselves in statistics and data science in a rigorous manner without leaving their day job and without compromising on quality,” adds Devavrat Shah, MIT professor in the Department of Electrical Engineering and Computer Science (EECS) who is both director of SDSC and a core faculty member of IDSS.

Learners obtain the MITx MicroMasters credential by completing online courses and a proctored test. “The MicroMasters will bring MIT’s rigorous, high-quality curricula and hands-on learning approach to learners around the world — at scale,” says Rajagopal. “For those who wish to advance their careers, the MITx MicroMasters will be a valuable professional credential. They will also be eligible to accelerate their completion of a PhD degree at MIT — or a master’s degree elsewhere.”

The program will launch in the fall, with enrollments opening June 5. Prospective students and interested institutions can sign up for updates from MITx. “This program embodies the IDSS vision of education in statistics and data science,” says IDSS Director Munther Dahleh, a professor in EECS. “We expect many universities to adopt this program as the basis for a masters program in data science.”

This fall SDSC and IDSS will also launch the Interdisciplinary Doctoral Program in Statistics (IDPS). IDPS is designed for students currently enrolled in a participating MIT doctoral program who wish to develop their understanding of 21st century statistics, using concepts of computation and data analysis as well as elements of classical statistics and probability within their chosen field of study.

IDPS students will take core classes in probability and statistics, as well as computation and data analysis courses that vary by home department. Participating departments include Aeronautics and Astronautics, Economics, Mathematics, and Political Science as well as IDSS’s own doctoral program in Social and Engineering Systems. Students’ dissertation research will use statistical methods in a substantial way.

The announcement of both new programs was made by Shah during opening remarks of SDSC’s annual Statistics and Data Science conference, which brought academic leaders, industry innovators, and rising stars in the fields of statistics and data science to MIT’s campus.


Topics: Classes and programs, IDSS, Massive open online courses (MOOCs), online learning, MicroMasters, EdX, MITx, Office of Open Learning, Data, Statistics, Machine learning, Aeronautical and astronautical engineering, Economics, Mathematics, Political science, School of Engineering, School of Humanities Arts and Social Sciences, School of Science, Electrical Engineering & Computer Science (eecs)

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