ONLINE COURSE
Applied Generative AI for Digital Transformation
Why enroll in this course?
Lead digital transformation in your organization by mastering the core concepts of generative artificial intelligence and its potential impact.
Master and integrate prompt engineering to optimize day-to-day tasks and automate workflows.
Foster an “AI friendly” culture in your organization by understanding the ethical aspects and the risks associated with the implementation of this technology.
Explore tools such as ChatGPT, as well as other emerging technologies, to improve productivity.
Interact with MIT experts, instructors, and peers in live synchronous sessions for a more comprehensive learning experience.
Access to rich supplementary resources provides additional materials and content for a more thorough educational journey.
What will you learn?
Learn about the history, development, and current applications of generative AI.
Learn the diverse applications of generative AI across fields such as art, biology, emotional support, and learning.
Understand and implement prompt engineering to improve productivity.
Learn strategies for automating organizational workflows with generative AI.
Understand the dynamics of reinforcement learning and the power of data search in generative AI.
Manage the ethics, compliance, and risks involved in utilizing generative AI.
Understand how generative AI can unlock new digital transformation opportunities for your organization.
Identify your organization’s technological and cultural needs to effectively leverage artificial intelligence.
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
The Applied Generative AI for Digital Transformation program explores how generative AI technology creates original and innovative content, driving an organization's digital transformation. Integrating technical expertise with management insights, ethical considerations, and human factors, this 8-week program offers a holistic understanding of digital transformation strategies powered by artificial intelligence.
Who is this online course for?
Senior leaders in charge of making decisions regarding generative AI initiatives in their organizations.
Technology leaders seeking to master the latest best practices for adopting and optimizing generative AI systems to enhance business outcomes.
Senior and mid-career executives interested in the potential applications of generative AI in their organizations.
Innovation managers, sales and product managers, and marketing and CX professionals seeking to leverage generative AI to create new products, content, and personalized customer experiences.
Venture capital, private equity, and/or pension fund investors interested in the investment opportunities created by generative AI.
Professionals from all industries and sectors interested in joining 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
Register now and boost your professional trajectory.
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