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Embedded AI Applications & Technologies
Course Description
Explore embedded AI by considering embedded AI applications, technologies, tools, and current trends in depth. Begin by reviewing applications that use AI to process video, audio, motion, and other signals. Review the details of the embedded ML models (including deep learning neural networks) behind some important applications. Study the highly specialized embedded ML software frameworks that are used to create intelligent embedded systems. Use some of these frameworks in hands-on explorations. Review the steps required to develop and deploy embedded ML models. See specialized devices for embedded AI, including new low power microcontrollers which incorporate neural network accelerators that will enable new battery-powered applications to execute complex ML models. Review the relevance of explainable AI and ethical AI for embedded AI. Conclude by exploring current trends and what may be on the horizon for embedded AI.
Prerequisite: EECS X480.1 Introduction to Embedded AI. Required hardware: Jetson Nano Developer 4G Kit.
Instructor
Textbook Information
Textbooks for your course may be purchased from any vendor or bookseller of your choice.
Required Textbook(s):
Learning Deep Learning: Theory and Practice of Neural Networks, Comput 9780137470358
Meeting Schedule
Event Date Day Start Time End Time Location Room
START 01/08/2024 Monday --- --- Online (Access Begins) ---
END 03/17/2024 Sunday --- --- Online (Access Ends) ---