Curious about any aspect of MIT Professional Education’s Applied Data Science Program? Hear about it first-hand from our alumni as they share on how joining the program impacted them and helped them achieve their professional goals.
The webinar is a great opportunity to understand the learning journey of MIT Professional Education’s Applied Data Science Program in detail and have your questions about the program answered through alumna's vast experience
Agenda for the session
- Insights on how to advance or transition your career in Data Science
- How the program can help you achieve your career goals in 2021
- Details of Live mentorship, hands-on learning and curriculum structure
About Speakers
Mr. Chad Barrett
Insights Analyst at Equinix
Chad Barrett is an Insights Analyst at Equinix. Apart from being an Economics major from the University of Manchester, Chad has dedicatedly pursued data-driven approaches in various stages of his career. He further also conducted independent research on machine learning and its business application at Cambridge. He joined the Applied Data Science Program by MIT Professional Education in 2020 as another step to advance his journey in the world of data-driven decision-making and will be seen sharing his experience on the same in this session
Mr. Milind Kopikare
President, Great Learning, North America
Milind Kopikare is the President of Great Learning, North America. An expert in digital transformation and customer experience management, he has a special interest in Data Visualization and Product Strategy. He has years of experience working at companies like Qualtrics, McKinsey and Google. Along with experience in managing and growing SaaS businesses, he has a passion for teaching and integrating technology into transformational education.
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.
