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 highschool students that suck at scientific subjects do on this a part of the world — Business studies.

My relationship with mathematics had been a slightly tumultuous one. I used to be an economics major in highschool. Physics left me feeling like I used to be in a parallel universe, and mathematical concepts gave the impression of secret codes from an alien civilization. Lessons took time to kick in, but.. they’d eventually kick in ultimately. Sometimes, very much later.

I knew very early on that carrying maths in my baggage would come in useful in some unspecified time in the future. So I used to be not going to let my scientific shortcomings prevent me from dreaming beyond my abilities. On the last 12 months of highschool, I made a decision to face the Math Monster once and for all. I invested all of my energy into taming the beast until it will definitely yielded.

It was a game-changing moment.

It gave me the essential confidence to later pursue a minor in Mathematics alongside my Business major during my university years.

Out of all the mathematics courses I pursued during my minor, these are the elemental ones that lay the groundwork for tackling Data Science and ML problems:

1. Calculus
2. Linear Algebra
3. Statistics & Probabilistic Theory

For all maths-fearing souls on the market, keep in mind that we only hate something to the extent of how poorly we perform in it. The earlier we improve and excel in a subject, the more our perception changes. So, in case your goal is to turn out to be 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 an excessive amount of getting tortured by the tantalizing clutches of the Math Monster. So in my final semester, I delved deep into exploring math-related profession paths. Ultimately my search led me to the sphere of Data Science. I seized a chance to intern as a Data Analyst and at the identical time, got into NYU’s Masters of Urban Informatics (a elaborate word for Applied Data Science in the sphere of Smart Cities).