| Date | Wednesday, July 30th, 2025 |
| Time | 7:00 AM (PST) | 10:00 AM (EST) | 11:00 AM (Brazil) | 4:00 PM (CET) | 6:00 PM (UAE) | 7:30 PM (IST) |
| Description | We are pleased to invite you on behalf of MIT Professional Education to participate in the “Virtual Open House on AI and ML: Leading Business Growth”. Join us for an exciting session featuring Devavrat Shah and Jehangir Amjad from MIT, who will share their expertise and research-driven insights while exploring the critical aspects of AI and ML in the context of driving business growth. This course empowers business leaders to understand and strategically implement AI. Demystify AI and unlock its transformative potential for your business. Learn how to leverage AI for strategic decision-making, organizational transformation, and building innovative products and services. |
The Webinar Will Cover:
- Learning journey and intensity of program curriculum
- Utility of the program for career progression and growth
- Value of peer learning and alumni network
- Question and answer session
Speakers
Devavrat Shah
Professor of Electrical Engineering and Computer Science, MIT
Director, Statistics and Data Science Center, MIT
Devavrat Shah is a professor with the Department of Electrical Engineering and Computer Science at MIT. He 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.
Jehangir Amjad
Lecturer, MIT Professional Education
Head of AI Platform at Ikigai Labs
Jehangir Amjad is the Head of AI Platform at Ikigai Labs and has been a Computer Science Lecturer both at Stanford and CSAIL at MIT, teaching courses in Machine Learning and Artificial Intelligence. 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. Jehangir received his PhD in Machine Learning from MIT and BSE in Electrical Engineering from Princeton University.