Focusing on the basics of machine learning and embedded systems, such as smartphones, this course will introduce you to the “language” of TinyML.
Applications Of TinyML
Get the opportunity to see TinyML in practice. You will see examples of TinyML applications, and learn first-hand how to train these models for tiny applications such as keyword spotting, visual wake words, and gesture recognition.
Deploying TinyML
Learn to program in TensorFlow Lite for microcontrollers so that you can write the code, and deploy your model to your very own tiny microcontroller. Before you know it, you’ll be implementing an entire TinyML application.
I attented tothe 2 first courses and I’m waiting for the 3rd one that start on 23 of February ! I wanted to thank you very much because I was quite new to ML and Python and now I’m able to write python code easily and I can write my own neural network by my self ! So thank you !!
It is great to hear that you were able to learn and grow Zloch. That’s exactly why we all worked hard on developing the course. Education, especially cutting-edge topics like TinyML, should be broadly accessible to everyone. I very much look forward to the day when folks such as yourself are teaching (Tiny) ML to others!
I have also completed the 2 courses. It is an excellent opportunity to get a hands on experience and enrich real-world challenges in AI/ML. I was a newbie to ML and DNNs, but these tailor made videos, reading and quizzes have helped me to evolve as learner and researcher of TinyML.
From the point of view of a new entrant in TinyML, learning the prior art in ML was quiet challenging. I wished if I could have got some more time, especially in Course 1, to comprehend these topics.
Also I think it would be great to have some collaborative coding assignments, which will involve coding from scratch,
Once again thanks for the awesome course experience
Good point. Feel free to create forum links in edX if you’d like to share something. Or folks could also use this Discourse forum as a place to share resources. We might have to create a edX course modules or something, but generally prefer to keep the edX discussions in the edX place – that said, this forum is for the community, so you folks should all decide what you wanna do
When you say collaborative, do you mean some sort of peer programming?
I’ve actually hired someone to setup a Discord server setup for real-time chatting and learning. But am keeping that quiet till we bootstrap the Discourse community first, otherwise too many distractions
Good point. Feel free to create forum links in edX if you’d like to share something. Or folks could also use this Discourse forum as a place to share resources. We might have to create a edX course modules or something, but generally prefer to keep the edX discussions in the edX place – that said, this forum is for the community, so you folks should all decide what you wanna do
Thanks. I will surely want to get back to Course 1 and understand the topics in more depth.
When you say collaborative, do you mean some sort of peer programming?
I’ve actually hired someone to setup a Discord server setup for real-time chatting and learning. But am keeping that quiet till we bootstrap the Discourse community first, otherwise too many distractions
Yes, I meant peer programming. The main point is to enable the students to build something from bottom up. In the assignments I found most of the template code provided, which is good to get started. But on the long run a hands on project, with a bare minimum template code, will prove to be useful.
Hi everyone - personally I found useful to have done CS50AI on edX prior to TinyML - to have the basis with python and general AI.
Completed 1 & 2 so far, looking forward to part 3!
I feel I learned much in these two courses - thanks to you Vijay and Lawrence! But also, I feel I got so much to learn and especially -train- on!
Any advice on how to train myself in being more fluent with the actual programming?
I currently try and replicate from scratch (as far as possible) the colabs we had during courses 1 and 2, and extending them a little, adding prediction and then try out some pictures / samples from the internet.
Thanks again for the chance to attend these courses.
Gotcha, we are thinking of how to ensure that you folks get to that point by the end of Course 3. We will have some template code, if possible, as starters for a project. Ultimately, we do want everyone to build their own projects! If you all have thoughts or suggestions, please feel free to share and drop them as ideas here or the Education category. We want to incorporate as much feedback as possible.
Completed and enjoyed very much first two courses and awaiting for the 3rd course Thank you VJ, Laurence Moroney and Pete Warden for this beautiful program!!
@vjreddi Can you extend the courses expiry dates or renew the courses after expire? I would like to review the course every month so that I can master the topics well.
I’d love to if it was under my control. There appear to be some generic rules around what content is available and for how long for different learners based on whether you are auditing the course or whether you are enrolled in the certificate program. Sadly, these things are out of my control and are edX rules.
That said, there is some hope! We will be able to release some of the slide material (not videos) under a copyright license, so stay tuned for that. Hope that gives you some assurance about going back and looking at the materials.
Yea, we will package it up in a shareable format. Thanks for the interest!
Personally, my hope is that folks are able to take the material and build on it and share it back with the community so that we can all build a learning machine that continues to give and share and grow.
While the quizzes/tests are not available after the audit period – all of the Colabs are accessible as I have hosted them through GitHub: GitHub - tinyMLx/colabs
To auto-launch each notebook in Colab all you need to do is change the URL as follows:
If the github link is: https://github.com/tinyMLx/colabs/blob/master/2-1-4-ExploringLoss.ipynb
Then the direct Colab link is: https://colab.research.google.com/github/tinyMLx/colabs/blob/master/2-1-4-ExploringLoss.ipynb
Hi Professor @vjreddi
I’m enrolled in TinyMl Professional Certificate. I’m currently on second Module (Applications). I’ve read that deadline for third course is April 25. I still did’t get my Arduino kit (maybe in somewhere in a shop or Brazilian customs).
I’m afraid that I’ll lost deadline for this third course. Is there a option to postpone this deadline or enroll in another session?
Thank you
