NVIDIA Launches Updated Teaching Kit for Edge AI and Robotics Educators

The NVIDIA Deep Learning Institute (DLI) Teaching Kit program released an updated 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.

Kit content

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

The hands-on labs and coding exercises are 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 not covered in the previous DLI Robotics teaching kit, which is now at end-of-life.

Educators downloading the kit also have the opportunity to purchase Jetson Nanos for teaching through a special program with SparkFun Electronics.

Modules

There are six major modules in this teaching kit:

Module 1: Introduction to Edge AI
Module 2: Vision Deep Neural Networks (DNNs)
Module 3: Diversity, Ethics, and Security
Module 4: Autonomous Robotics
Module 5: Reinforcement Learning
Module 6: Natural Language Conversational AI

Learn more with GTC On-Demand

At the recent NVIDIA GTC, attendees had the opportunity to learn about this new teaching kit. NVIDIA principal technical marketing engineer Dustin Franklin, along with faculty from the University of Oxford and UMBC, presented highlights from the kit: Getting Started with the Edge AI and Robotics Teaching Kit.

Both Oxford and UMBC are already using the content in their curriculum.

“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.

“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,” said Patty Delafuente, adjunct professor at UMBC, whose team also helped create the teaching kit.

The contents of the kit are designed to teach students studying computer science, engineering, and other disciplines benefiting 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.