With edge machine learning positioned as a leading emerging technology, a robust workforce will be needed to fill the category’s demands. Edge Impulse, the leading provider of edge machine learning tools, has launched its university program to help train students to fill these roles. Designed to enable graduate and undergraduate classes to teach edge and embedded machine learning, the program provides free and open instructional content to professors and teachers, along with access to cutting-edge hardware tools.
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In the university program’s launch in 2022, Edge Impulse gave away over 3,000 Arduino TinyML Kits, along with slides, videos, and hands-on exercises, to schools in 70 different countries, helping integrate edge and embedded machine learning into university curriculums. Now the university program returns for 2023 with another Arduino Kit giveaway to help build on their commitment to accessible and affordable tools for students and educators.
Edge Impulse has worked with leading schools and companies to develop and support the program, including Harvard’s John A. Paulson School of Engineering and Applied Sciences (SEAS), the Abdus Salam International Centre for Theoretical Physics (ICTP), Arduino, and Nordic Semiconductor.
Some of the schools that have already joined the program include UCLA, Purdue, US Air Force Academy, UPenn, University of Helsinki, TU Delft, Trinity College Dublin, University of São Paulo, Syracuse University, CU Boulder, UT Austin, Texas A&M, University of Houston, University of Nevada, Las Vegas, Georgia Tech, Arizona State University (ASU), Harvey Mudd College, Carnegie Mellon University, and University of Maryland, College Park (UMD).
“The future of machine learning is tiny and bright,” said Prof. Vijay Janapa Reddi of Harvard University. “Edge impulse makes it easy to onboard learners and helps them get started with embedded ML.”
“Edge Impulse comes to our rescue, helping the electronics, computing, and control and automation students to abstract frameworks, such as TensorFlow, to gather data and deploy trained models into embedded devices,” said Prof. Marcelo José Rovai of Universidade Federal de Itajubá. “Edge Impulse supported our students in all steps of their edge machine learning projects.”
SOURCE: PR Newswire