The science of recommendation systems exemplifies how technology streamlines these various decision-making processes for us. In fact, as Prof. Devavrat Shah (Massachusetts Institute of Technology) suggests, Recommendation systems take into account several statistics and machine learning topics and allow you to build on them. Watch this masterclass for a deep dive into one of the most intriguing technology today.

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Agenda for the session

  • Intro to Recommendation systems
  • Overview of MIT faculty for the ADSP Program
  • hands-on projects, & mentorship from industry practitioners

About Speakers

Mr. Prof. Devavrat Shah

professor with the department of electrical engineering and computer science, MIT

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 Faculty Director of the MicroMasters in Statistics and Data Science program at IDSS. Prof. Shah was awarded the first ACM SIGMETRICS Rising Star Award 2008 for his work on network scheduling algorithms. He received the 2010 Erlang Prize from INFORMS, which is given to a young researcher for outstanding contributions to applied probability. 

Mr. Milind Kopikare

President of Great Learning at North America

Milind Kopikare is the President of Great Learning at North America. prior to that, he was the VP and Head of Product for the Experience Management product at Qualtrics. Here he took a product from zero to a $300 Mn ARR and created a whole new product category. Milind has also consulted Fortune 500 executives during his time at McKinsey and was par of the Android team at Google. He has an MBA from Kellogg, a MS from Stanford and a B.Tech from IIT Bombay.

MIT Professional Education's Applied Data Science Program

The Applied Data Science Program curriculum has been carefully crafted by MIT faculty to provide you with the skills, knowledge, and confidence you need to flourish in the industry. By encompassing the most business-relevant technologies, such as Machine Learning, Deep Learning, Recommendation Systems, and more, it prepares you to be an important part of data science efforts at any organization.