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NVIDIA Releases Teaching Kit For Edge AI And Robotics Educators

The Edge AI and Robotics Teaching Kit is a collaborative effort between NVIDIA experts, a team from the University of Oxford, and the University of Maryland, Baltimore County (UMBC).

The NVIDIA Deep Learning Institute (DLI) Teaching Kit Program recently announced the release of a new course for university educators to teach the latest in edge AI and robotics. The Edge AI and Robotics Teaching Kit is a collaborative effort between NVIDIA experts, a team from the University of Oxford, and the University of Maryland, Baltimore County (UMBC). As the fifth release from DLI, the kit complements existing deep learning, accelerated computing, and accelerated data science teaching kits.

Students will be learning through a combination of lecture slides, hands-on labs, and teaching materials centred around edge computing, deep learning, the Internet of Things, video analytics, and autonomous robotics.

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The hands-on labs and coding exercises would be run on Jetson Nano, exposing students to parallel computing and powerful embedded platforms used in many of the world’s most advanced robots and edge devices. This new kit explores areas and concepts which were not covered in the previous DLI Robotics Teaching Kit, which is now at end-of-life. 

There are six major modules in this teaching kit, starting with:

  • ​​​Module 1: Introduction to Edge AI​ 
  • ​​​​​Module 2: Vision Deep Neural Networks (DNNs​)
  • Module 3: Diversity, Ethics, and Security
  • Module 4: Autonomous Robotics

The last two modules will be available in a future release of the kit:

  • Module 5: Reinforcement Learning
  • Module 6: Natural Language Conversational AI

“Codeveloping these materials with NVIDIA helped us expand our AI syllabus with PyTorch—a key deep learning computing framework. We also plan to integrate Jetson into other aspects of our syllabus. We look forward to working on the next release with NVIDIA to enable educators and classrooms worldwide with these important technologies,” said Ajit Jaokar. An AI Course Director at Oxford, Jaokar and his team collaborated on kit development.

Adjunct Professor at UMBC, Patty Delafuente, whose team also helped create the Teaching Kit, said, “The content we developed has enabled UMBC to provide students with hands-on experience working with innovative, cutting-edge AI technology and world-class educational materials. We incorporated working versions of the content in our graduate course Data 690: Applied AI for Practitioners in Spring 2021.”

The contents of the kit are designed to teach students studying computer science, engineering, and other disciplines benefitting from edge AI and robotics courses. It can be taught to students ranging from first-year undergrads to third-year graduate students.

The Teaching Kit is freely available for educators as an open-source package to integrate into their courses and teaching curricula. Students are encouraged to ask their instructors to join the DLI Teaching Kit Program.

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Victor Dey
Victor is an aspiring Data Scientist & is a Master of Science in Data Science & Big Data Analytics. He is a Researcher, a Data Science Influencer and also an Ex-University Football Player. A keen learner of new developments in Data Science and Artificial Intelligence, he is committed to growing the Data Science community.

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