Machine Learning is the future of coding, and in the last couple of years, more of our advanced students are focusing on it. Ask a Computer Science major what they want to go into. I bet it is ML.
Parents frequently ask us “is my son or daughter ready for the Machine Learning focus?” Or even more general, “what is the path for a middle schooler who doesn’t know how to code now, but sticks with Breakout Mentors for multiple years?”
Let’s explore it and hear about the learning experience of two actual Breakout Mentors students.
What is Machine Learning?
Simply put, machine learning is the process of using data to make predictions. The incredible part though is that the computer “learns” the relationship from the data on its own. When you can’t find the pattern in the data yourself, a machine learning algorithm can often do it for you.
It is used everywhere from autonomous driving, diagnostics from medical images, spam detection, finance, weather prediction, robotics, and many more. Yes, data can be almost anything stored on a computer: images, video, audio, text, numbers.
What are the Breakout Mentors Offerings for ML?
Since 2020, we have offered the Machine Learning and Artificial Intelligence Academy for our advanced students. There are two options for this track. It can either be done during the school year with our standard weekly 90-minute session format or more concentrated over the summer through our Deep Dive program.
Either way, the goal is to take students with zero experience in the fundamentals through neural networks to make amazing projects. We customize the learning to each student’s background and interests. This often means glossing over the complex mathematics unless a student is interested. We also often find custom datasets about topics the student is interested in.
Students will learn how to create and train their own machine-learning models. Projects include:
Automatic Bank Check Processor — converts handwritten text into digital form using images of the text for automated bank check processing.
Automatic Pneumonia Detection — detects pneumonia using chest x-rays to help doctors provide better diagnoses and help patients receive proper care.
CoPoet — writes poetry in the style of your favorite poet using automatic text generation from the prompts you provide.
Artificial Intelligence Small Group Workshops
One of the most exciting things about artificial intelligence and the field of machine learning is that you don’t necessarily have to be an expert to achieve amazing results. There are incredible tools that have already been built that are freely available — for example, ChatGPT for a chatbot.
It is possible to interact with these AI tools through code, even for beginners. This workshop is a great way to gain exposure to artificial intelligence and make some exciting projects that motivate students to want to learn more.
That’s why we created the Hands-On AI App Development Workshop, which is limited to 4 students. This workshop allows each student to have the code they are working on, with the mentor able to provide individual instruction as needed. We have also found this size helps participants feel comfortable speaking in a group discussion.
We typically run the 3.5-hour group workshop once a month on the weekend. Join our Artificial Intelligence and Machine Learning-specific email list to be notified when registration opens for future workshops.
Is the Machine Learning Academy Right for Me?
Breakout Mentors works with a wide range of ages and levels of coding experience. So, no matter the student’s background and goals, we will identify the best starting place.
In order to start on the ML track, we require 6 months of coding experience and comfort with algebra. The field of data science is distinct enough from high school computer science and mathematics that we’ll cover what beginners need to know. We typically do not really get into the calculus and linear algebra aspects of ML.
For students who don’t have the right coding foundations, we will start with standard Python Computer Science. We have mentors on our CS track who maintain a challenging pace of learning and cover the coding key concepts necessary for ML.
We also have some students who already took an advanced AI course. Once the student is familiar with the foundations of ML, we focus on Capstone Projects. These projects, chosen by the student, are ambitious and can take a month or more to complete. Capstone projects are an excellent way for students to apply their knowledge to active research problems in ML and are a great addition to their college applications or resume.
Some examples will help. Let’s get to know some actual students.
Jace: An 8th Grader Coding Seriously for 1 Year
We crafted a personalized learning path for Jace that consisted of learning the foundations of machine learning through small to intermediate-level projects. As this was the first time she had exposure to machine learning techniques, it took about 12 sessions of meeting with her mentor to complete the foundation curriculum. Upon completing the curriculum, she built an automatic hand-digit recognition app for recognizing characters on bank checks. Jace began the summer with zero prior machine learning skills and ended the summer with a full toolbox of skills and the ability to build intermediate machine learning projects from scratch. For students like Jace we focus on developing a deep understanding of fundamentals while building fun small to intermediate-level projects, leaving them motivated to continue advancing their skills.
Dylan: An 11th Grader Who Already Took AP CS A
Dylan is an incoming 11th grader. He has been coding since 8th grade. He has taken AP CS P and A and is comfortable coding in object-oriented languages such as Java and Python. He recently completed pre-calculus and is entering AP Calculus this school year. He has experience building intermediate to advanced Python coding projects like Space Invaders and Pacman. He’s taken a few weekend courses on machine learning but would like to further his understanding of the field. He has a passion for psychology and the brain and would like to apply machine learning methods to help people live better, happier lives.
Dylan came into our Machine Learning Summer Deep Dive with prior machine learning, computer science, and math experience. We tailored the curriculum to meet his skillset and goals. First, we reviewed the foundational material with him, and he built small hands-on projects to deepen his understanding of core machine learning concepts. Then, we developed a project plan aligned with his interest in psychology and would take his skills to the next level. He and his mentor worked for 7 sessions building out a machine learning app that could extract emotional sentiment from tweets and classify the emotional character expressed in each tweet. For students like Dylan, we focus on developing projects from scratch, learning more complex algorithms like Deep Learning, and applying what they learn to topics they are interested in to develop project portfolios for internships and college applications.
Get Started Now!
It is shocking how busy high school students are these days. The natural reaction is to push off things we want to do until there is more time. Unfortunately, free time is elusive: there is no better time than now.
Please contact us here to discuss if your son or daughter is a good fit for machine learning and how to get started now.