Machine Learning: From Data to Decisions

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This program takes a look at machine learning through a lens of practical applications. It is designed specifically for decision makers who want to harness the power of machine learning and effectively manage the team of data scientists who make it possible.

By the end of the course, participants will be able to develop a competitive edge by turning what is unknown into what's known—leading to better business decisions and outcomes. Regardless of where you are on the spectrum of machine learning adoption---and, more broadly, artificial intelligence---this online program provides the latest thought leadership in machine learning tools and techniques.

Machine learning: From Data to Decisions requires no prerequisites in terms of math or computational sciences, although some basic experience with statistics is helpful.

English Language Course (Learn more)

  • February 4, 2020 - April 7, 2020 (Register Now!)
  • May 7, 2020 - July 9, 2020 (Registration opens February 12)

Spanish Language Course (Learn more)

  • February 18, 2020 - April 14, 2020 (Register Now!)
  • April 21, 2020 - June 16, 2020 (Registration opens February 26)

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About the Instructor

Dr. Devavrat Shah
Professor of Electrical Engineering and Computer Science and Director of Statistics and Data Science Center

Devavrat Shah Devavrat Shah is a professor with the department of electrical engineering and computer science, MIT. He is a member of the Laboratory for Information and Decision Systems (LIDS) and Operations Research Center (ORC), and the Director of the newly formed Statistics and Data Center in Institute for Data, Systems, and Society. His research focus is on theory of large complex networks, which includes network algorithms, stochastic networks, network information theory, and large-scale statistical inference.