LIVE VIRTUAL COURSE
Applied Generative AI for Digital Transformation
This course is not currently available in the live virtual format. We invite you to explore the course in the online format, with the same instructors and materials - available now for enrollment.
Live Online Learning Experience
Immerse yourself in interactive sessions and meaningful conversations led by MIT experts.
Elevate your understanding through insightful one-hour Q&A sessions after each live session.
Access a trove of additional content and resources, offering a comprehensive learning experience.
To unlock your organization's full potential.
Play an essential role in optimizing workflows in your organization.
Through emerging generative AI techonology.
What will you learn?
Understand generative AI deeply, including its historical development
Discover how diverse domains like art, biology, emotional support, and learning apply Generative AI
Comprehend and implement prompt engineering to enhance productivity
Learn strategies for automating organizational workflows using Generative AI
Understand the dynamics of reinforcement learning and the power of data search in Generative AI
Navigate the ethical, compliance, and risk aspects associated with Generative AI
Harness the power of Gen AI in addressing real-world business challenges
All the participants who successfully complete their program will receive an MIT Professional Education Certificate of Completion, as well as Continuing Education Units (CEUs)*.
To obtain CEUs, complete the accreditation confirmation, which is available at the end of the course. CEUs are calculated for each course based on the number of learning hours.
*The Continuing Education Unit (CEU) is defined as 10 contact hours of ongoing learning to indicate the amount of time they have devoted to a non-credit/non-degree professional development program.
To understand whether or not these CEUs may be applied toward professional certification, licensing requirements, or other required training or continuing education hours, please consult your training department or licensing authority directly.
Course outline
Applied Generative AI for Digital Transformation program is a focused three-week live virtual course designed to explore generative AI technologies in depth. This course seamlessly combines technical knowledge with managerial perspectives, ethical considerations, and human factors, providing a comprehensive understanding of digital transformation strategies leveraging AI as a driving force for change.
Who is this virtual course for?
Senior leaders grappling with the potential opportunities and challenges of generative AI for their businesses
Technology leaders who want to learn current best practices for adopting and optimizing generative AI systems to boost business outcomes
Senior managers and mid-career executives who want to gain insights into the potential applications of generative AI within their organizations
Innovation managers, sales and product managers, and marketing and customer experience professionals who want to learn how to leverage generative AI to create new products, new content, and personalized customer experiences
Investors in venture capital, private equity, or hedge funds looking to understand investment opportunities created by generative AI
Professionals from all industries and sectors are welcome to create a dynamic learning ecosystem
Prerequisites: No prior background in analytics, computer science, coding or machine learning is required.
Instructors
Professor of Information Engineering, Civil and Environmental Engineering and Director of MIT Geospatial Data Center, and a faculty member in the Center for Computational Science and Engineering part of the Schwarzman School of Computer Science
Executive Director of MIT’s Geospatial Data Center, Research Scientist; Center for Complex Engineering Systems, Sociotechnical Systems Research Center, under the Schwarzman School of Computer Science
Faculty contributor
Professor in MIT's Department of Electrical Engineering and Computer Science; Head of Computer-Assisted Programming Group and Associate Director and COO of MIT Computer Science and Artificial Intelligence Laboratory
MIT research contributor
MIT Research Contributor
Industry contributors
Chief Information Officer of The Boeing Company and Senior Vice President of Information Technology and Data Analytics
CIO and Enterprise Strategist at Amazon
Deputy Chief Security Officer at GitHub
