How Learning Data Science Changed My Life and Can Change Yours Too

A little motivational post on how learning data science changed my life for the greater good, and hopefully, it can inspire yours too

Photo by Randy Tarampi on Unsplash

Table of Contents

  1. The Emergence
  2. The Evergrowing Motivation
  3. The Final Words

The Emergence

Perhaps like many of you, growing up I didn’t know what I wanted to do. Whether it’s music, fitness, or art, we all had hobbies and interests, but only some had a strong desire to turn their hobbies into their career.

I was always good at math, some would call me a mathemagician. At 17, I went to college blindsided and started majoring in Electrical Engineering at The Grove School of Engineering at CCNY. Learning about nanotechnology was cool, but it wasn’t exactly what I was looking for. On the morning of my 18th birthday, I went ahead and signed my name away to the military — something that I’ve been waiting to do, but wasn’t legally eligible to due to my age. All other cool things aside, this was where I started to gain more interest in computers. Even until this day, I miss such a lifestyle, but memories live on.

After coming back from the Army, I moved out of NYC and decided to go back to school. Without knowing anything about coding, I switched majors to computer science. Initially, it wasn’t very interesting for me, but I knew I was interested in computers. After a semester, I decided to change my major to computer engineering and things started to get more interesting. Within a few semesters, life outside of college started to get more difficult. My limits started to get tested and I started to flunk in school. As things started getting better, the damage was already done in academics and I decided to drop out of the engineering school at UB.

Though this devastated me at the time, looking back at it today, this was one of the best decisions I’ve ever made as it opened new doors for me. Yet once again, I changed my major, but this time to Computational Mathematics because I had most of the requirements already completed for the degree.

One of the courses required to finish the degree was MTH 448 which was only offered once a year. I didn’t have the prerequisites for the class because I needed to know Python. It was unfeasible for me to wait another year to take the class so I reached out to the professor who was teaching it, and he allowed me to enroll in the course as long as I learned Python before the course started, and so I did.

The Evergrowing Motivation

Because I had some coding knowledge at that time, learning Python was very easy, and I started to like coding again because of Python. I even started doing small projects to get better at it — something I didn’t initially have the inspiration to do with other languages.

It wasn’t until the course started, where my inspiration picked up exponentially, thanks to Dr. Ringland — the professor teaching the course. Before starting the class, I didn’t know anything about machine learning or data science, so I was afraid that the course would be the hardest one I was taking that semester.

The way Dr. Ringland taught the course wanted you to go back. Every lecture transitioned into the next very smoothly, it was like a memorable tv-series. One of my close friends was also taking the course with me. The class which I once thought was going to be the hardest for that semester, turned out to be the only class I looked forward to, thanks to the professor and the friend.

Dr. Ringland motivated me in such a way that I continued to learn more about what we can do with data even after the course ended. It amazed me how data can be used to upgrade our standards of living: increasing life expectancy, automation, more profitable business decisions, just to name a few. The more I learned about data science, the more I started to connect things in life and realize patterns. I started to gain knowledge of things in several different fields from simply doing exploratory data analysis alone.

Data science is being used today in many astounding ways. If you told me 10 years ago that data science is used to help give football (soccer) teams a tactical advantage over the opposing team, I’d have no idea what you’re talking about, but if you told me this 5 years ago, I’d be a bit shocked and interested to learn more. The art of data science is even being applied right now as I’m writing this article, thanks Grammarly.

Back in high school, a close friend and I once had a discussion on whether it’s better to know a lot about a few things or know a little about a lot of things. We both agreed to the latter, and personally, I think Data Science is a mix of both, which is why I can’t see myself not continuing to grow in this field. I’m not only allocating a lot of my time to learn about a certain field, but I’m also figuratively “killing two birds with one stone” by applying one field to other fields.

The Final Words

With the technological advancements we have today, data is growing exponentially. Andrew McAfee summarizes data growth nicely,

“The world is one big data problem.”
- Andrew McAfee

More small businesses and companies are realizing the importance of analyzing data. This means that the need for people to make data useful is also growing. If you’re interested in wanting to be a part of the community that brings use to data, makes data meaningful, or even if you’re interested in wanting to find ways to collect data (of course in compliance with privacy laws), it’s never too late to start. Well… I always like to tell myself the old cliché, tomorrow is already too late. And remember, you had to first walk in the pool (or ocean or whatever you’re into) before you learned how to swim.

You don’t have to do this alone either. I had a teacher and a friend to keep me motivated long enough before having the desire to learn on my own. You don’t have to pay to get a teacher. There are plenty of free resources online for you to learn from. I also suggest that you learn with a friend to stay motivated. If your friend isn’t interested, you can always share this article, or even give your reasoning as to why your friend might find this field interesting down the line. Chances are, you guys are going to work different jobs. You might be interested in becoming a data scientist and your friend might be more interested in becoming a data analyst. What will happen in the future doesn’t matter, but the main key is that you guys started together and motivated each other to find a new purpose.

Looking back at it today, it amazes me how my desire to play with data emerged. Numbers would once tell me stories, but now I make stories out of numbers.

After learning about how data can be used for the greater good (of course it can go both ways), I’m glad I chose to continue on this journey, and I aspire to help make the world a better place. Though my original perspectives of life are still present, learning about data science transitioned me into starting to view certain things in life through different lenses — and I think that’s powerful, which is why I want to have a strong ambition to inspire and motivate others to learn and continue learning about data science.

As I’m writing this on the 11th of November, Happy Veterans Day to all!

If you enjoyed reading this article, follow me on Medium and Kaggle where I’ll be posting more content from time to time. Also, feel free to connect with me on LinkedIn.

As always, thanks for stopping by.

Stories will come as time goes by | Computational Mathematics Grad | Ambition to inspire others |