Machine Learning for Embedded Systems with ARM Ethos-U NPU Free Coupon

Learn AI, ML, and TensorFlow Lite for microcontrollers with ARM NPU
5 (54 reviews) 1,804+ students
Instructor: Wadix Technologies Published by: Subham (MOD) English

Course Description

Machine Learning for Embedded Systems with ARM Ethos-U

Are you ready to bring the power of machine learning into the world of embedded systems?
This course takes you on a complete, hands-on journey from building and training models to running them on real ARM-based hardware with dedicated NPUs.

Most ML courses stop at theory or training. This one goes further: you’ll actually deploy and run models on embedded devices, bridging the gap between machine learning and practical engineering.

What you’ll learn

The core ML theory behind embedded AI

  • Understand the stages of a neural network execution pipeline

  • Explore convolution, flattening, activation functions, and softmax in CNNs

  • Learn how ML operations are optimized for resource-constrained devices

Model preparation workflow

  • Train models in TensorFlow

  • Convert them into lightweight .tflite models

  • Optimize and compile with the ARM Vela compiler for the Ethos-U NPU

Running inference on embedded devices

  • Execute models with TensorFlow Lite Micro (TFLM) in C++

  • See how ML operations map to CMSIS-NN kernels and the Ethos-U hardware accelerator

  • Understand the complete inference path — from model to silicon

Hands-on with real hardware

  • Set up and run the Alif E7 ML Development Kit

  • Build and deploy Keyword Spotting and Image Classification demos

  • Observe real-time outputs directly on the device

Why this course is unique

  • Bridges the gap between ML theory and real embedded deployment

  • Covers the entire workflow — from training to NPU execution

  • Practical, hardware-driven approach using the Alif E7 ML dev kit

  • Projects designed for easy reproduction on a Windows machine

By the end of this course, you’ll have the confidence and skills to run ML models efficiently on modern embedded systems, skills that are in high demand across IoT, robotics, and edge AI applications.

Whether you’re an embedded engineer ready to add AI to your skill set, or a machine learning practitioner eager to deploy models on hardware accelerators, this course will give you a competitive edge in the future of AI and embedded systems.


Enroll now and start building the next generation of embedded AI applications!

Review: Our Opinion

Everything You Need to Know About Machine Learning for Embedded Systems with ARM Ethos-U NPU

This course is a comprehensive and well-structured introduction to Machine Learning for Embedded Systems with ARM Ethos-U NPU. The instructor, Wadix Technologies, is a leading expert in the field with a wealth of experience in IT & Software to share.

The course is well-structured and easy to follow, and the instructor does a great job of explaining complex concepts in a clear and concise way.

The course is divided into sections, each of which covers a different aspect related to Other IT & Software. Each module contains a series of video lectures, readings, and hands-on exercises.

The instructor does a great job of explaining each topic in a clear and concise way. He/She also provides plenty of examples and exercises to help students learn the material.

One of the things I liked most about this course is that it is very practical. The instructor focuses on teaching students the skills and knowledge they need to succeed in the real world. He/She also provides students with access to a variety of resources, including templates, checklists, and cheat sheets.

Another thing I liked about this course is that it is offered on Udemy. Udemy is a great platform for taking online courses because it offers a lot of flexibility for students. Students can choose to take courses at their own pace, and they can access the course materials from anywhere with an internet connection.

Udemy also offers a variety of payment options, so students can find a plan that works for them. The course also has a very active community forum where students can ask questions and interact with each other. The instructor is also very responsive to student questions and feedback.

Overall, I highly recommend this course to anyone who is interested in learning Machine Learning for Embedded Systems with ARM Ethos-U NPU. It is a well-organized and informative course that will teach you the skills and knowledge you need to succeed.

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