Approximating an Education, Part One: High School

One day in Sixth Grade, in my Sixth Grade classroom with my Sixth Grade teacher, I sat down at our computer during lunch hour and started researching University programs. For myself. I didn’t really have anything else to do, and so that was my idea to fill the time: I would eat my peanut butter sandwich, and I would map out my entire life course for the next 50 years. That is the kind of kid I was, and that was exactly how badly I wanted to be an adult and have my life figured out. Apparently I simply couldn’t enjoy a game of tetherball with my fellow 11 year olds with my future existing out there as a complete unknown.

So that day I decided I wanted to be an Accountant.

And that dream lasted for about 3 months, before I discovered Sports Journalism. After Sports Journalism, it was being a Musician. And this carried on for about 4 years, as I grasped at potential life course after potential life course. That was when I admitted defeat; I realized that trying to find my passion in life as a kid in school was a pointless exercise, an impossible endeavor. So I stopped trying. And then, I discovered what I wanted to be.

Around the time I was 14, I got really into fantasy football. For those of you that don’t know, it’s a game you play with friends where you construct a roster of football players from the NFL, and get points (and thus wins and losses) based on their statistical performance. It’s sports for nerds. And I was a nerd that also happened to be a huge sports fan. So in preparation for one of our annual drafts, I decided to make an Excel workbook where I could look at all the NFL data from the past season to help make my team. I had never really used Excel before, but through this project of mine (which, by the way, I worked on through all of Spring Break, which is 5 months before the season even starts) I started to learn some things about the program. You can write formulas. You can make fancy charts. You can learn information from data.

I came third-last that year and my team was awful, but that didn’t matter much; one, because I was still enjoying it, and two, because I was gaining something far more valuable than bragging rights and money, which was a real interest in learning. Next year came around and I picked up where I left off on my new spreadsheet tool, armed with a year of experience and a lot more knowledge about what Excel could really do. I made tons of changes to the workbook, added a whole bunch of new stuff, and came 2nd in my league. I had a new hobby, and it was making spreadsheets.

So I knew how to manipulate information and present it to myself visually and extract some minor insights by staring at the data for a while. But I knew there was math to be done here, somehow. I had no idea what math that was, but I saw a screen full of numbers that had the power to help me make more objective decisions, if I could only figure out how to make it do that. The bottom line was: I needed to take a Stats class. So having figured that out, I pulled up Google, and did the following search:

Udacity, EdX, Stanford Online. Could this be my gateway to the future?

I clicked the top link because, well, it was on top, and I immediately dove into the first unit: Scatter Plots. And slowly, but surely… I fell asleep. Man those units are boring. But I powered through, because I knew there was information here somewhere, and eventually Sebastian started talking about Bayes Rule and my ears perked up. I finished the course during my spare time from 11th grade, in about 2 months. I could have gone straight back to my Excel workbook and plugged in what I knew to my analysis, but I really enjoyed taking that course, and I wanted to take more. So I did.

Intro to Computer Science; Intro to Descriptive Statistics; Intro to Inferential Statistics. I was getting a sneak peek of first-year college, for free, from my bedroom. And it was fantastic. I still did well in “real” school, but my real attention and focus was on Udacity. As I dug deeper into these courses, I started to notice a theme, which was that they were all tagged with the category “data science”. I had no idea what that was, but I thought it sounded like a pretty good name for what I was doing. Turns out, in a few days it might be my job title. But we’ll get there.

Over the summer I made another round of improvements to my Excel workbook, while at the same time wondering what other tools were out there. But I was really good at Excel now, and I had figured out how to do most of what I wanted it to do, so I stuck with it. That was until eventually, I stumbled upon the Udacity course called “Exploratory Data Analysis with R”. I didn’t know what R was, but I found it online, downloaded it and something called RStudio, and started playing around. Turns out, it’s a programming language for doing things with data. And guess what? It is miles ahead of Excel. It was at this point that I started realizing what Data Science actually was.

Oh, and so to finish off the Excel part of this story: I enrolled in a class in 12th grade called the Microsoft Academy, where I got certifications in all the Office programs, including Excel. I did well enough on Excel that I was named the Canadian National Champion for Excel. I went to Dallas, and competed in the Microsoft Office Specialist World Championships (“Nerd Olympics”, for short). I came 2nd to a guy from Singapore, and won some money. Thus concludes the Excel portion of the story. If you Google something along the lines of “Nash Taylor excel”, you can read more about that than I’m willing to put words to here. Can we get back to R now?

So while all that was happening, I was continuing to progress with R, to the point where I had scripts that were apparently cool enough that I could go downtown into Vancouver to meet with Microsoft employees (courtesy of a connection through my Microsoft Academy teacher) and make them go “HOW old did you say you were?” by projecting the scripts onto a screen. So that was neat. We’re at the point in the story now, by the way, where not only do I know what data science is, but I’m actually starting to learn how to do it, and I know where to go to learn more about it (Udacity, and as I would start to figure out, the internet in general). That was good timing, because this is also the part of the story where I graduate high school and have to decide what I want to do for post-secondary education. This is the moment I’ve been thinking about since Sixth Grade.

So where did I go after high school? Any guesses?