Online Summer Program Launched to Support CS Ed in the COVID-19 Era

One Student Shares Her Journey with CS and Explains the Innovating Thinking to Launch an Online Summer Program for Students Passionate About Machine Learning and AI

Image for post
Image for post
Julia Camacho, 2019

My very first computer science project was nothing more than a cat gliding across my computer screen. The Scratch cat, to be specific — and the fact that I was able to achieve something so monumental (well, in my eight-year-old eyes at least) with only a couple of simple drag-and-drop blocks amazed me.

Fast forward ten years, now I’m conducting machine learning research and developing computational tools for cancer diagnosis and treatment. I wish my younger self could have taken a peek at where the field of computer science was headed, but my current self knows that even what I’m doing right now is only the tip of the iceberg. Every day, advancements in computer science shape another aspect of our lives. The machine learning and artificial intelligence revolution has only really just begun.

I began learning how to code in elementary school after being introduced to JavaScript and Python. I spent hours creating my own little animation and GUI projects, fascinated by the shapes and colors that popped up on my screen after writing only a few lines of letters and numbers. In middle school, however, I discovered that I also had a strong interest in another field of science seemingly distant from computer science — biology. Yearning for a way to combine my two interests, I was thrilled to discover the burgeoning field of computational biology. I instantly felt right at home: here was a way to analyze biological concepts with the logical approach that I loved about computer science. I began learning the fundamentals of data science and developing my own research projects. As I continued to learn about the latest advancements in computing and data science, I became fascinated with machine learning and artificial intelligence. Their power to discover patterns in data that once seemed impossible to interpret unlocked a whole new plane of thinking.

Image for post
Image for post

When I entered the Texas Academy of Mathematics and Science (TAMS) in my junior year of high school, I was able to work as a research assistant in a biostatistics laboratory at the University of North Texas. There, I used machine learning and AI to develop computational tools for cancer diagnosis, analysis, and treatment. At the Academy, I also met many classmates who were also passionate about computing and AI. Excited by the possibilities of using our shared knowledge and experience to educate our community, two of my friends and I decided to found the TAMS Artificial Intelligence Society. Throughout the year, we held weekly meetings where we taught our classmates how machine learning algorithms worked as well as how to implement them in Python and create impactful projects for social and scientific good. We realized how important it is to truly understand the mathematical and computational mechanisms behind these algorithms and the consequences that arise if data scientists and researchers aren’t careful to develop programs responsibly. The entire world is becoming increasingly reliant on algorithms to help run areas of our lives ranging from healthcare to transportation to criminal justice, and if we don’t truly understand how these algorithms work, we run the risk of being controlled by them, instead of the other way around.

Image for post
Image for post

To address this, we decided to launch a summer program online due to COVID-19 for students passionate about machine learning and AI. Through AI for Aspiring Researchers, we aim to teach the fundamentals of machine learning from the ground up, focusing on the math and computational thinking behind AI algorithms. Through weekly lessons, we will be covering eight different algorithms and machine learning concepts — ranging from decision trees to neural networks to reinforcement learning — and at the end of the eight weeks, we will guide students in writing their own research review paper over a specific algorithm or concept that they found interesting. We hope that through our program, students will gain a deeper understanding of the math and algorithms behind machine learning and become more confident navigating the ever-expanding world of computer science and AI research.

About the Author: Julia Camacho is an incoming undergraduate student at the Massachusetts Institute of Technology, where she will be majoring in computer science and molecular biology. She is passionate about computational oncology and believes that machine learning and AI will revolutionize healthcare. Julia is an Intel International Science and Engineering Fair grand prize winner, an American Junior Academy of Science fellow, and an NCWIT Aspirations in Computing national award winner. In her free time, she enjoys watching political dramas and playing piano and tennis.

Written by

The national hub for the Computer Science for All movement, making high-quality computer science education an integral part of K-12 education in the US.

Get the Medium app

A button that says 'Download on the App Store', and if clicked it will lead you to the iOS App store
A button that says 'Get it on, Google Play', and if clicked it will lead you to the Google Play store