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Step 1 — Facing & Embracing the Math Monster
Despite a long-standing fascination for science, God had yet not deemed me deserving of the highly exclusive gift of deciphering scientific jargon easily. Nor was I blessed with perfect pitch either, but this has nothing to do with this.
So, anyway, upon graduation, I naturally gravitated towards what most clueless high school students that suck at scientific subjects do in this part of the world — Business studies.
My relationship with mathematics had been a rather tumultuous one. I was an economics major in high school. Physics left me feeling like I was in a parallel universe, and mathematical concepts sounded like secret codes from an alien civilization. Lessons took time to kick in, but.. they would eventually kick in sooner or later. Sometimes, very much later.
I knew very early on that carrying maths in my baggage would come in handy at some point. So I was not going to let my scientific shortcomings prevent me from dreaming beyond my abilities. On the last year of high school, I decided to face the Math Monster once and for all. I invested all of my energy into taming the beast until it eventually yielded.
It was a game-changing moment.
It gave me the necessary confidence to later pursue a minor in Mathematics alongside my Business major during my university years.
Out of all the math courses I pursued during my minor, these are the fundamental ones that lay the groundwork for tackling Data Science and ML problems:
- Calculus
- Linear Algebra
- Statistics & Probabilistic Theory
For all maths-fearing souls out there, remember that we only hate something to the extent of how poorly we perform in it. The sooner we improve and excel in a subject, the more our perception changes. So, if your goal is to become a badass Data Scientist, it’s time to confront the Math Monster head-on and show him who’s the boss!
Business was clearly not meant to be my calling. I enjoyed way too much getting tortured by the tantalizing clutches of the Math Monster. So in my final semester, I delved deep into exploring math-related career paths. Ultimately my search led me to the field of Data Science. I seized an opportunity to intern as a Data Analyst and at the same time, got into NYU’s Masters of Urban Informatics (a fancy word for Applied Data Science in the field of Smart Cities).
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