Hi, my name is Ashley Leal, I'm one of the 2026 Edge Impulse Campus Ambassadors, helping run workshops, hackathons, and more, to promote edge AI.
As part of the WISE National Conference 2026 in January, I had the opportunity to lead a hands-on Introduction to Edge AI workshop for around 30 students from a wide range of educational backgrounds and levels of machine learning experience.
The goal of the session was simple: to show that building and deploying edge AI systems is not only possible but also approachable — even without prior experience in ML or embedded systems.
A Hands-On Experience
I really wanted this workshop to be interactive, not just a lecture. Rather than focusing solely on theory, the workshop was designed to be interactive and practical from start to finish. Participants worked through the Edge AI pipeline using Edge Impulse, taking a project from raw data they collected themselves all the way to deployment on real hardware.
During the session, students:
- Built and labeled their own image datasets using mobile data collection
- Explored how dataset quality and variation impact model performance
- Created an Impulse for feature extraction and training
- Evaluated results and discussed overfitting, underfitting, and tuning hyperparameters
- Learned the concept of quantization to optimize for resource constraints
- Discovered how easy it is to deploy the final model to an Arduino UNO Q for on-device inference
For many participants, this was their first time building an ML model. Seeing it run successfully was definitely the highlight of the workshop!
Meeting Students Where They Are
One of the most rewarding aspects of the session was seeing students with very different levels of ML experience engage meaningfully with the material. Some participants had prior exposure to machine learning, while others were encountering these concepts for the very first time.
The Edge Impulse platform played a critical role in this accessibility. By abstracting low-level implementation details, students were able to focus on understanding the big picture — the end-to-end workflow and constraints — all without needing to write a single line of ML code.
Empowering the Next Generation of Builders
There’s something powerful about building something tangible yourself from start to finish. Workshops like this demonstrate how powerful hands-on learning can be, especially in emerging technology areas that may initially seem intimidating, like edge AI. Giving students the chance to build real, deployable systems not only demystifies the field but also builds confidence to keep exploring — whether that’s in IoT, healthcare, or beyond.
A huge thank you to WISE UofT for creating a space that uplifts women in technical fields, to Qualcomm for the opportunity to lead this workshop as a company representative, and to Edge Impulse for making edge AI education so accessible for students. Most of all, I’m grateful for the students — for their curiosity, their courage, and their willingness to try something new.