Students program scale race cars to zip around a track while vying for the fastest time By Chris Clay on July 4, 2025
In addition to the programming skills needed to get the car navigating the track, other skills were utilized. Initially, some of the models were leaving the track. So, Shah and his team used their collective leadership skills to ensure everyone stayed motivated and on task while tapping into their problem-solving skills needed to fix the issue.
“I’m certainly glad that I joined AWS DeepRacer,” said Shah. “It was an amazing experience and a valuable one for a student taking Artificial Intelligence with Machine Learning. We really enjoyed it and were having so much fun they had to tell us to go home one night because we had stayed so late working.”
Mihai Albu is a professor with the Faculty of Applied Sciences & Technology and a researcher at Humber. He’s overseeing Humber’s AWS DeepRacer competition that was expanded this year to include, for the first time, teams from Cambria, Conestoga, Seneca and George Brown colleges.
In total, more than 65 students across 15 teams were at North Campus for the competition.
Albu said the competition is valuable for learners as they develop their programming skills while gaining practical experience.
It also teaches the students about the concept of reinforcement learning, which is a ML technique that trains software to make decisions to achieve the most optimal results. The students learn as they experiment with different parameters in the programming and can see the results of their decisions in real time based on how their model does on the lap.
