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Driving Digital Transformation with Applied Generative AI
Artificial Intelligence is revolutionizing various sectors by automating processes, analyzing large volumes of data, and providing valuable insights. Among the many branches of AI, generative AI stands out for its ability to create new content, from text and images to music and software code, based on patterns learned from existing data.
Generative AI now enables the automation of complex tasks that were previously exclusive to humans. Companies in sectors such as marketing, healthcare, finance, and entertainment are using this technology to innovate and improve operational efficiency. As generative AI continues to evolve, its potential to drive innovation and efficiency across various sectors is only expected to grow, redefining the future of work and business.
$7.9 trillion
Generative AI could have an economic impact of up to $7.9 trillion per year.
Source: McKinsey
94%
of business executives believe that AI is a key to success in the future.
Source: Deloitte
78%
of executive leaders believe that the benefits of generative AI outweigh the risks.
Source: Gartner
An online course designed to enhance your generative AI expertise
MIT Professional Education’s online course Applied Generative AI for Digital Transformation explores the complexities of generative AI, providing participants with advanced knowledge and tools to drive digital transformation, improve efficiency, and create new pathways for innovation.
The skills you will develop
This 8-week course helps participants understand generative AI and its evolution, equipping them with the knowledge and confidence to make effective decisions, while driving innovation and digital transformation within businesses. This AI course provides key theoretical and practical tools to optimize productivity and business growth in an efficient and automated way.
1.
Understand and explain the historical context behind artificial intelligence, including its origins and foundational concepts.
2.
Harness the latest generative AI tools to automate workflows and increase productivity in the workplace.
3.
Leverage prompt engineering principles to enhance organizational performance and drive results.
4.
Employ generative AI for domain-specific tasks such as video summarization, automated research, and conversational data understanding.
5.
Identify opportunities, ethical considerations, and potential challenges in digital transformation through the application of generative AI.
6.
Minimize risks, protect data privacy, and enhance the customer experience by utilizing Gen AI technologies and tools.
In addition, you will receive a Certificate of Completion
All the participants who successfully complete the online course Applied Generative AI for Digital Transformation will receive an MIT Professional Education Certificate of Completion. Furthermore, participants will receive * MIT 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.
This course is aimed at
Senior leaders responsible for guiding generative AI initiatives and shaping key decisions for their organizations.
Technology leaders seeking to master the latest best practices for implementing and optimizing generative AI systems to drive organizational success.
Senior managers and mid-career executives looking to discover potential opportunities for generative AI in their organization.
Innovation managers, sales and product managers, and marketing and customer experience professionals who want to learn to harness generative AI to develop new products, craft compelling content, and deliver personalized customer experiences.
Investors in venture capital, private equity, or hedge funds seeking to uncover new investment opportunities fueled by generative AI advancements.
Meet the instructors of this course
Professor John R. Williams’s research focuses on the development and application of computing algorithms in distributed cyber-physical systems. He was director of the Auto-ID Laboratory, where the Internet of Things was invented. In 2005, he was considered, aBrochures with Bill Gates and Larry Ellison, one of the 50 most powerful people in “Computer Networks.”
He is the author and co-author of more than 250 articles in journals and conferences. Professor Williams teaches courses on the basics of programming, modern software development, and the architecture of Web, cloud, and blockchain systems.
Dr. Sanchez is the architect of The Internet of Things global network and data analysis platforms for SAP, Ford, Johnson & Johnson, Accenture, Shell, Exxon Mobil, and Altria. In cybersecurity, he has developed cyberattack impact analyses for the U.S. Department of Defense and designed a password firewall for the IARPA.
Dr. Sanchez holds a PhD from the Massachusetts Institute of Technology (MIT) and teaches MIT courses in cybersecurity, engineering, blockchain, and data science. He has been involved in developing educational software for Microsoft and establishing the Accenture Technology Academy. He has produced over 150 educational videos, has 10 years of experience with learning management systems, and has made deployments in the Americas, Asia, and Europe.
