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Discovering Data Science with Amy

It's almost November, and the season for underclassmen to decide apply for summer programs. I had the opportunity to partake in UCLA’s Pre College Summer Institute. The course I took was a month long, in person, data science program called Computer Science Summer Institute – Intermediate Track. This was my experience.

Illustrated by Lily Jiang

By Amy Zhao


My first day of the program was not the one I had expected. After trekking over half an hour around the maze of a campus and getting swindled by the charismatic homeless man by the bear statue, I finally found the lecture hall tucked behind a series of giant monoliths.

Entering the lecture hall for the first time was somewhat exciting. The rows and rows of swing-arm chairs were way too many for the 50 of us. From then on we got to meet the professor and our TAs, all students and staff of UCLA. And then our lecture began.

I believe the others were as daunted as me for this first day. After some brief overviews, the professor suddenly bombarded us with equations with 20 symbols and concepts that I didn’t even know where to begin processing. Even the TAs could tell our fear as the head TA sent out a very thoughtful letter reassuring us.

After a dazed 3 hours, I met up with my cohort’s TA and found myself in a more comforting environment of a standard classroom. This program is similarly structured to a real class in college, where you first attend a lecture and then a discussion class (ours were portioned into 8 students each). In this class, my TA magically taught us all the lecture content in the span of an hour without making my brain hurt. The concepts really seemed so simple with their help, even those scary equations were easy to understand after breaking them down. The remaining 2 hours of class served as office hours, where you could stay and ask questions or do homework, or just simply leave.

The homework consisted mostly of guided coding, breaking it down step by step. What we learned was different compared to the coding learned in a typical CSP or CSA class in that you do not learn skills that fundamentally improve your coding, but a completely different set of skills catering to the data science life cycle. The coding part of this course was pretty hands off, as you have to know a substantial amount of Python in order to register and you are expected to learn the majority of the new coding techniques on your own. But of course, the TA will provide assistance for even the smallest of problems.

The coding which we learned was the same being used in the data science industry. All of the homework assignments were also very practical and ranged from data cleaning, prediction modeling, data classification, and much more all on real world datasets.

Despite the help from the TA in discussion class, lectures still felt difficult and tedious. I noticed that as the days went on, fewer and fewer students were attending the lectures. By last week, only 30 students showed up. Since they do not take any attendance, it was up to you whether or not you would go to lecture and class, much like a real college course.

The Final Project

Our final project was a group project (4-5 people) on any subject we wanted. After carefully considering our options my group settled on rice image classification, both because it was funny and due to the diminutive nature of rice that is near indistinguishable to the eye.

Alongside of our models we also had to write an ACM formatted report as if we were trying to publish it as a real report. I took on the task of one model and compiling this report and I read many rice classification reports to aid in my research.

Though these reports were initially purely for me to understand formatting and writing style, I was surprised to be able to understand everything they were saying. All of the models and processes from the course appeared and I was surprised how immediately applicable my knowledge was.

After finishing up the project we all presented them on the last day. I am pleased to report that my team received 3rd place and I won a free UCLA water bottle at a ridiculous price ($30).

Was it Worth it?


The program with its additional fees is about $3000. If you choose to go on campus that is an additional $2,300, with meals provided. However, financial aid is offered if you are eligible. I would heavily recommend going in person as the campus experience heavily differs from a stay-at-home one. Since the curriculum is modeled off of a real college course, being able to live in dorms, walk to classes, experience the city on the weekends, etc., all contribute to a taste of the college experience, especially the UCLA one. Additionally, the course teaches all of what you would learn if you took a similar class in college, along with many practical applications to hone your skill. So if you’re a high schooler looking for a data science course with a little college experience on the side, this is a program that I would highly recommend.

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