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Learners Enrolled : 19
Created by Gettobyte
English & Hindi
This course is a hands-on guide to developing and deploying AI/ML applications on NXP microcontrollers and processors using the powerful eIQ™ Machine Learning Software Development Environment. Designed for embedded system engineers and AI developers, this course walks you through the complete Edge AI workflow—from training models on the host PC to running them in real-time on low-power NXP hardware.
Focusing entirely on the NXP ecosystem, you’ll explore how to use the eIQ Toolkit with inference engines such as TensorFlow Lite Micro, CMSIS-NN, ONNX Runtime, and DeepViewRT. You’ll train, optimize, and deploy AI models for MCU and MPU platforms including the S32K3xx, and the i.MX93 with integrated Ethos-U65 NPU.
Using the JupyterLab-based eIQ interface and NXP Edge AI boards, you’ll build real-world projects such as fault detection in smart meters, predictive maintenance on industrial sensors, and lightweight image classification on embedded vision systems. You’ll also learn how to optimize AI models for performance, power efficiency, and memory footprint using NXP’s toolchain.
Through labs and capstone projects, this course enables you to create intelligent, connected, and efficient embedded systems—completely within the NXP Edge AI platform.
Learn live with top educators, chat with teachers and other attendees, and get your doubts cleared.
Our curriculum is designed by experts to make sure you get the best learning experience.
Interact and network with like-minded folks from various backgrounds in exclusive chat groups.
Stuck on something? Discuss it with your peers and the instructors in the inbuilt chat groups.
With the quizzes and live tests practice what you learned, and track your class performance.
Flaunt your skills with course certificates. You can showcase the certificates on LinkedIn with a click.
Launch your Graphy
