Join us for a virtual open house to learn more about the MIT Professional Education AI and ML: Leading Business Growth program.

This program is designed to empower business leaders with the knowledge to strategically understand and implement AI. Demystify AI's concepts and unlock its transformative potential for your organization. You will gain skills to leverage AI for strategic decision-making, organizational transformation, and the development of innovative products and services.

MIT instructors Professor Devavrat Shah and Jehangir Amjad will be presenting, offering an in-depth overview of the immersive learning experience, the curriculum, and who stands to benefit most from participating.

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Agenda for the session

  • Learning journey and curriculum
  • Networking and career application
  • Measurable outcomes
  • Q&A session

About Speakers

Devavrat Shah

Professor of Electrical Engineering and Computer Science, MIT

Devavrat Shah is a member of the Laboratory for Information and Decision Systems (LIDS) and Operations Research Center (ORC), and the Director of the Statistics and Data Science Center (SDSC) in IDSS. His research focus is on theory of large complex networks, which includes network algorithms, stochastic networks, network information theory and large-scale statistical inference. Prof. Shah was awarded the first ACM SIGMETRICS Rising Star Award 2008 for his work on network scheduling algorithms. 

Jehangir Amjad

Head of AI Platform, Ikigai Labs

Jehangir Amjad has been a Computer Science Lecturer both at Stanford and CSAIL at MIT, teaching courses in ML and AI. He was awarded the Jerome H. Saltzer Award for Excellence in Teaching at MIT. Jehangir joined Ikigai from Google where he was a Software Engineer where at first he helped build and deploy distributed pipelines for statistical inference to help make Google’s global networking infrastructure increasingly more robust and reliable. He then joined the open source Data Commons project at Google which represents the largest knowledge graph of public data.

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