The Xavier High School teams won 2nd place and 3rd place respectively in the recently concluded Yale-NUS Data Science Competition, organized/hosted by Yale-NUS College, the National University of Singapore, and Yale University and sponsored by Airbnb, Sence and NUS Enterprise.
Note: The 1st place went to a team of Junior College and Secondary school students from Singapore and Vietnam (Bandung American International School, Hwa Chong Institution, and Catholic Junior College) . Their winning case looked at the dataset of housing in Boston.
The 1st Runner up (2nd Placer) team worked on global migration patterns based on average salary income per country (read their interview below), while the 2nd runner up team worked on Video game sales (https://www.kaggle.com/gregorut/videogamesales ) and what, if any correlations it had with crime rates ( http://www.disastercenter.com/crime/uscrime.htm) graph shown below:
The Xavier teams competed against other teams from high schools, junior colleges and universities from Singapore, and Vietnam. Each team were given 6 hours to present data insights and groundbreaking solutions given their chosen datasets. Here is what Steven Justin Sy, Grade 11 XS, who did the OFW case and won 2nd place said:
What inspired you to join this competition?
I spend a lot of time on the internet, and whenever I browse through the front page of Reddit, without fail, there will always be technological innovation to be found, whether it be artificial organs, self-driving cars, machine learning, and the like.
These are always the kinds of things that have inspired me, and when the opportunity to learn about them on a deeper level, to find out how they work and listen to people experienced in that field, presented itself, I couldn’t resist taking it.
What project did you do and what insights did you learn from it?
Our group conducted Insulae Nostrum, which means, “Our Islands”, which used data science to analyze sets of data about overseas Filipino workers (OFW’s), infant mortality, wages, and tax rates to examine the correlations between these factors and the flow of workers abroad.
Curiously, from the data we gathered, we found that the main factor that OFW’s consider when deciding the country they move to isn’t wages, but rather, tax rates. This finding was supported by correlational studies.
What inspired you to do the project you did?
Our group wanted to look into the lives of these OFW’s, to find out what makes them who they are and do what they do.
Do you have any tips for fellow high school students who want to get into data science?
Data science is a broad field of study. To do data science is to do justice to the world, to look at it from the perspective of facts and figures, of objective reasoning. The key thing to note here is that data science shouldn’t be considered an exclusive field of study, but one that applies to everyone. Before this competition, I had little to no skills in Python, but I found that other skills from other fields of study such as sociology and economics played a part in our participation in this competition, eventually allowing us to pull through.
Sean Saito, main facilitator and organizer (Code Gakko) shared about the event:
We realized that Singapore is in a unique place as a growing data science hub not only in SEA but also in the world. The government has recognized that it is the most relevant field in computer science today as it provides the greatest breadth in application. Machine learning and AI influence automobiles, medicine, business analytics, game development, and much more.
I was incredibly amazed by how much the participants were able to pick up in just a short time. Most students had no Python experience. But in less than 24 hours, each team was able to generate plots and conduct statistical analysis on real datasets. Talk about going from zero to hero!
Code Gakko posted a video of this event here: