Update: We're currently revising the content for this program. Check back in late 2023.
We use artificial intelligence (AI) every day, from the predictive text on our phones to finding the best route with a GPS, but its application to industries like manufacturing and logistics is still emerging.
To help industrial fields incorporate AI into their business practices, the University of Washington is partnering with Microsoft to offer a new three-course program, Autonomous AI for Industry, on the online learning platform Coursera. All three courses are now available and open for enrollment.
In this new addition to our massive open online courses, or MOOCs, you’ll learn how to apply machine teaching techniques to autonomous AI systems to improve industrial processes. You’ll understand the important role subject matter experts play in training advanced AI. By the end of the specialization, you’ll know how to design and build smarter, more agile control systems that are ready for real-world application.
"I was excited to collaborate with the UW on this specialization because the field of autonomous AI has tremendous potential as a new tool for automation, and we want to empower a broad and diverse population,” said Kence Anderson, lead instructor of the Autonomous AI for Industry specialization.
UW on Coursera: Autonomous AI for Industry
Hear more about The University of Washington's new program on Coursera: Autonomous AI for Industry.
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STUDY WITH AUTONOMOUS AI EXPERTS
The specialization is taught by some of the world's leading experts in autonomous AI and machine teaching. In addition to being the program's lead instructor, Kence Anderson is also the director of the autonomous AI adoption team at Microsoft. He's designed more than 150 autonomous AI systems for Fortune 500 companies and is the author of the book Designing Autonomous AI: A Guide for Machine Teaching.
Juan Vergara is a senior applied AI engineer at Microsoft, where he leads the technical Bonsai Advance training for partners and customers. John Alexander is the developer and engineer relations lead in autonomous systems at Microsoft. He's passionate about designing and building accessible experiences using machine learning coupled with vision, voice, touch and virtual/mixed reality. Teresa Escrig is a principal project manager on the autonomous AI adoption team at Microsoft. She developed the specialization's quizzes and milestones as well as strongly influenced the structure of the courses. She also leads the autonomous AI architect training for partners and customers.
LEARN AT YOUR OWN PACE
Autonomous AI for Industry is self-paced. You can start each course instantly and set deadlines according to your schedule. At the suggested pace of four hours a week, this specialization takes around four months to complete.
The specialization also presents the material in a variety of formats, a feature that Marjorie Adriaenssens, a lead industrial metaverse architect at Microsoft who completed the Machine Teaching for Autonomous AI course, appreciated.
"There are videos, written assignments, pop quiz–like exercises — having all of that together means there's something for any type of learner."
SHOWCASE YOUR NEW SKILLS
You'll receive a certificate after completing each individual course. Once you've completed all three courses, you'll receive a specialization certificate. You can showcase your certificates on your LinkedIn profile, resume or CV.
“Having this specialization on your resume demonstrates that you have not only learned the skills but that you’ve applied them to building an autonomous AI system that works,” said Anderson.
EXTEND YOUR LEARNING
Interested in continuing your AI learning? Take a look at UW’s other MOOCs on Coursera and edX .