The benefit of learning together with your friend is that you keep each other accountable and have meaningful discussions about what you're learning.
Courtlyn
Promotion and Events Specialist
Learn the strategic impact and application of automation
June 22, 2022
6 weeks
4–6 hours per week
Our participants tell us that taking this program together with their colleagues helps to share common language and accelerate impact.
We hope you find the same. Special pricing is available for groups.
The benefit of learning together with your friend is that you keep each other accountable and have meaningful discussions about what you're learning.
Courtlyn
Promotion and Events SpecialistBased on the information you provided, your team is eligible for a special discount, for Automation for Digital Transformation starting on June 22, 2022 .
We’ve sent you an email with enrollment next steps. If you’re ready to enroll now, click the button below.
Have questions? Email us at group-enrollments@emeritus.org.For senior business leaders, functional managers, and automation engineers who want to leverage automation to make their organizations more competitive, this program provides a foundational understanding of how automation can improve efficiency and effectiveness across your organization. The global artificial intelligence (AI) market is forecasted to reach USD 185.17 billion by 2026 at a compound annual growth rate (CAGR) of 39.7%.
In this program you will:Schedule a call with one of our academic advisors.
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Learn the language of automation and become familiar with the basic mechanisms of robot software architectures, machine learning, and simulation system.
Trace the evolution of dialogue systems by examining the capabilities, limitations, and mechanisms, and explore opportunities to implement a dialogue system at your organization.
Discover the market trends and commercial applications of cutting-edge automation technologies in manufacturing with a special focus on collaborative robotic (cobots) systems.
Recognize the market size and growth of autonomous drones and understand their enabling technologies, commercial applications, and business value
Explore the commercial applications, state-of-the-art technology, and near-term possibilities of autonomy and automation in transportation and logistics.
Assess the strategic, economic, and social impacts of automation and devise actionable plans to prepare for the future of work.
Learn the language of automation and become familiar with the basic mechanisms of robot software architectures, machine learning, and simulation system.
Recognize the market size and growth of autonomous drones and understand their enabling technologies, commercial applications, and business value
Trace the evolution of dialogue systems by examining the capabilities, limitations, and mechanisms, and explore opportunities to implement a dialogue system at your organization.
Explore the commercial applications, state-of-the-art technology, and near-term possibilities of autonomy and automation in transportation and logistics.
Discover the market trends and commercial applications of cutting-edge automation technologies in manufacturing with a special focus on collaborative robotic (cobots) systems.
Assess the strategic, economic, and social impacts of automation and devise actionable plans to prepare for the future of work.
Live Q&A Session with MIT Faculty
Recorded Video Lectures
Discussion Groups
Application Exercises
Office Hours with Subject Matter Experts for Added Support
Peer Networking Opportunities
Continuous Program Access for Up to 12 Months
Analysis of Real-World Companies
Sertac Karaman
Daniela Rus
David Autor
Jim Glass
Julie Shah
Sertac Karaman
Faculty Lead
Sertac Karaman is the Director of the Laboratory for Information and Decision Systems, Associate Director in the Institute for Data, Systems, and Society, and Associate Professor of Aeronautics and Astronautics at MIT. His research interests lie in the broad area of embedded systems and mobile robotics. His recent research has focused on developing planning and control algorithms for autonomous vehicles and autonomy-enabled transportation systems. More broadly, he has worked on driverless cars, unmanned aerial vehicles, distributed aerial surveillance systems, air traffic control algorithms, certification and verification of control systems software, and many others. In particular, he was a member of the MIT team that built a self-driving car and competed in the DARPA Urban Challenge in 2007. His experience with robotic platforms also includes developing an autonomous forklift, working with Willow Garage’s personal robot PR2, and developing fully autonomous agile drones. He has published more than one hundred technical articles in the area of autonomous vehicles. He is also Co-founder of Optimus Ride, an MIT spin-off company based in Boston that develops self-driving vehicle technologies to enable efficient, sustainable, and equitable mobility.
Daniela Rus
Faculty Lead
Daniela Rus is the Andrew (1956) and Erna Viterbi Professor of Electrical Engineering and Computer Science, Director of the Computer Science and Artificial Intelligence Laboratory at MIT, and Deputy Dean of Research in the Schwarzman College of Computing at MIT. Rus' research interests are in robotics and artificial intelligence. The key focus of her research is to develop the science and engineering of autonomy. Rus is a Class of 2002 MacArthur Fellow, a fellow of ACM, AAAI and IEEE, a member of the National Academy of Engineering, and of the American Academy of Arts and Sciences. She is the recipient of the Engelberger Award for robotics. She is a senior visiting fellow at MITRE Corporation. She earned her PhD in computer science from Cornell University.
David Autor
Instructor
David Autor is Ford Professor in the MIT Department of Economics, codirector of the NBER Labor Studies Program, and coleader of both the MIT Work of the Future Task Force and the JPAL Work of the Future experimental initiative. His scholarship explores the labor-market impacts of technological change and globalization on job polarization, skill demands, earnings levels and inequality, and electoral outcomes.
Jim Glass
Instructor
James Glass is a Senior Research Scientist at MIT where he leads the Spoken Language Systems Group in the Computer Science and Artificial Intelligence Laboratory. He is also a member of the Harvard-MIT Health Sciences and Technology Faculty. His research focuses on automatic speech recognition, unsupervised speech processing, and spoken language understanding using machine learning. He is an IEEE Fellow, a fellow of the International Speech Communication Association, and an associate editor for the IEEE Transactions on Pattern Analysis and Machine Intelligence.
Julie Shah
Instructor
Julie Shah is associate dean of Social and Ethical Responsibilities of Computing at MIT, a Professor of Aeronautics and Astronautics, and director of the Interactive Robotics Group, which aims to imagine the future of work by designing collaborative robot teammates that enhance human capability. She is expanding the use of human cognitive models for artificial intelligence and has translated her work to manufacturing assembly lines, healthcare applications, transportation and defense. Before joining the faculty, she worked at Boeing Research and Technology on robotics applications for aerospace manufacturing.
Prof. Shah has been recognized by the National Science Foundation with a Faculty Early Career Development (CAREER) award and by MIT Technology Review on its 35 Innovators Under 35 list. Her work on industrial human-robot collaboration was also in Technology Review’s 2013 list of 10 Breakthrough Technologies. She has received international recognition in the form of best paper awards and nominations from the ACM/IEEE International Conference on Human-Robot Interaction, the American Institute of Aeronautics and Astronautics, the Human Factors and Ergonomics Society, the International Conference on Automated Planning and Scheduling, and the International Symposium on Robotics. She earned degrees in aeronautics and astronautics and in autonomous systems from MIT.
Get recognized! Upon completion of the program, MIT Schwarzman College of Computing grants a certificate to successful participants.
Download BrochureFlexible payment options available.