Our students learn science while creating products that benefit the community. They design and perform their own investigations whether it's a physics, chemistry, biology, or engineering class. Their designs focus on real world problems. They interview the "client" and design based on the needs they have identified.
Ours is a diverse student body in almost every sense.
As a group, they represent every socioeconomic strata in our city. A hands-on approach to science and technology keeps them engaged and motivated.
Our students are learning how to program in python, a powerful computer language used in machine learning. We always look for ways to apply new skills in real-world hands-on applications. One of the most interesting and engaging examples of machine learning today is self-driving cars.
When kids see self-driving cars in the news, they immediately want to know, "how do they do that".
To pull this off, we will start with a robotic car that includes a processor powerful enough to run machine learning models. We will then add cameras and sensors so that students can "teach" the cars to recognize objects and navigate to and around them without user intervention. The QPi system is based on a Raspberry Pi. It has enough compute power and can accommodate a wide range of external sensors to serve as the basis for our "smart" car.
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