Learner Reviews & Feedback for Introduction to Embedded Machine Learning by Edge Impulse

The Course is really Helpful for me. It just gave me a good and basic idea of where to start if i want to implement machine learning in the microcontroller.

Very good arrange of topics and explain complex topics as simply as possible. Recommended course for anyone who needs to start in embedded machine learning.

ML on embedded systems is an exciting and growing technology and business domain. This course is a great place to start learning about it.

Excellent course with great foundational knowledge about machine learning on edge devices using your smart phone and the Arduino Nano 33 BLE Sense for hands-on, real world, applications that are enabled on the Edge Impulse machine learning platform. Shawn did an excellent job putting together the course curriculum and presented a complete and comprehensive set of knowledge, including lectures given by Alexander on machine learning and artificial intelligence, and also information and 'labs' for students to complete that made it easy to apply the concepts taught in this course. I highly recommend this course using the Arduino Nano 33 BLE Sense for real world applications if you'd like to know what's under the hood of embedded IoT devices. 👍

This is an exceptional introduction to machine learning on embedded devices.

The material covers all the bases and leaves you with a very good idea of what is involved. The use of Edge Impulse allows rapid prototyping of machine learning solutions so the course is able to walk you through two working examples, a movement gesture classifier and an audio keyword classifier, that you can deploy to either a mobile phone or an Arduino board. In addition two projects allow you to have a go for yourself.

Whilst the course doesn't delve too much into the heavy theory it does provide plenty of resources where you can look for additional information. It also includes a wealth of top tips that will help you with your ML projects.

This course was very useful. I am not new to Machine Learning and microcontrollers and have been developing tinyML models. I have even been playing with EdgeImpulse, but this course teaches you the whole machine learning data pipeline from data collection. through data cleaning, train/validation/test split, data augmentation, feature engineering, model creation, model training and tuning, fixing fitting problems and finally, deploying the solution to your hardware.

It helped me to see the process as a whole!

Thanks a lot!

This course dives you through the basic knowledge of embedded machine learning. The way instructor Shawn Heyml taught the course was just awesome. The most interesting thing about this course was that some concepts were taught by the experts in their respected domains. If you are looking for some new course in the embedded systems domain then this course is perfect for you. I would like to thank my instructor Mr. Shawn Heyml who have done great efforts to clear each and every concept through this course.

An excellent course to step into the world of embedded machine learning and TinyML. Despite being a 3 week course, it manages to fit in a lot of relevant content including ML basics, sensor data processing, and feature selection.

The instructors do a great job of clearly communicating the concepts without assuming any prior knowledge of Embedded Systems and Machine Learning. The teaching materials used are also top-notch and effective.

Very good course! I've started this course having absolute zero knowledge about AI, machine learning and related stuff. Now, I can say I do know the basics of AI and machine learning, allowing (and encouraging) me to deep dive into these areas to make more and more interesting embedded systems projects..

Shawn Hymal is an excellent instructor! This course was a great introduction to TinyML. I learned a lot about working with Edge Impulse. Building and deploying embedded machine learning applications is exciting. I am looking forward to courses using advanced microcontrollers and edge impulse.

If you want to do a machine learning project using embedded systems and you need to start from the basics, this is the place you are looking for! I 110% recommend this course to all the beginners who want to learn ML, speaking from my personal experience.

Great course for ML beginners, like me! Not covering all the complex math behind but giving you a high level introduction. Showing what is possible with ML (and what is not). I especially liked the "Hands-on" training part based on Edge Impulse.

This course was very useful for me as I'm just starting in the field and was having trouble with more practical concepts. It was great that you took the time to clarify the things most likely to go wrong

even though I was already an edge impulse user, I learned a lot of things I didn't know thanks to this course. Special mention for Shawn as an excellent professor

The videos and supplemental materials were well-presented and very useful. The hands-on projects were the best for learning practical use of the concepts.

Thanks for the great course! The explanations are excellents, the examples and activities give me insights for use embedded ML in my projects.

A great introduction to tinyML and embedded machine learning using Edge Impulse to get started working on projects immediately.

Great Course to get into machine learning, Shawn is a great teacher and reading recommendations are great!

This is a perfect and practical introduction to embedded machine learning. Learned a lot! Thank you.

Very good course to learn about Machine Learning as stand alone as well as ML with Embedded system.

Short and sweet course. A very lucid introduction to the beautiful world of TinyML. Thanks.

Great intro to ML on embedded devices that also introduces basic machine learning concepts.

Short and Quick to follow and try the same using EdgeImpulse website with actual projects

Great course for introduccion, and they gave yo a lot of extra information in lectures.

Than you for the Course. I hope that we can have Videos Pdf files.

Best Regards