Interest in Machine Learning is quickly growing amongst our students and mentors. Ask any Computer Science student what they want to do when the graduate, and you are likely to hear ML or related terms (deep learning, AI, etc.).
So what is it? To fully get into it, we have an upcoming webinar on Thursday, April 8th at 5pm PDT! Sign up here.
The webinar is hosted by our ML Director Kai Middlebrook along with another education organization, A4. We will explain how it works going from data to “learning” to output (predicting, classifying, generating, and more). And we’ll go through many impressive examples based on things our actual students are creating!
Why are High School Students Excited about ML?
It is mind blowing what you can accomplish with a few lines of machine learning code. It isn’t easy developing the right model by understanding which algorithm or approach to use, however it is simple once you do.
For example in our introductory materials students build a handwritten digit recognition model. It classifies what you wrote, just like when you scan a check at the ATM.
Many high school students are interested in working on real-world projects. Things like analyzing images of lung scans to identify damage from COVID. Or real-time deforestation in the Amazon. Or using a video feed to train the dog to stay off the couch even when you aren’t home.
Machine learning enables these projects and more.
Summer Learning with Breakout Mentors
We believe year-round learning is important, but during the summer we also allow students to take advantage of the more hours available to make rapid learning progress. So we have a team of mentors available to run Deep Dives into Machine Learning and other types of coding (Scratch, Python, USACO, etc.) for $1800. These are usually either 3 hours a day for 1 week or 90 minutes a day for 2 weeks.
Our Machine Learning specialist this summer is an impressive student at UC Berkeley who has been on our team for the last year. He helps run the ML club on campus, training other Cal students on exciting projects. Over the summer he’ll use the perfect blend of Breakout Mentors structure plus open ended projects — starting with the 15 hour Deep Dive, then continuing with capstone projects.