I Want to Become a Data Scientist

So 3 months ago, I decided that I want to become a data scientist. How? I didn’t know yet. Why? Because I really wanted to.

When I turned 30, I realized that I’m not in a path to achieve my full potential. Ever since I graduated I have worked in the tech industry, first as a software engineer and then as a business analyst. In my early 20s I thought I should explore different areas and not be stuck in just one thing, like coding, or testing or project management. So I switched roles, gained a lot of experience but this took a good amount of time because before i knew it, I was turning 30. Now there’s nothing wrong with this approach in my head. But most people would expect you to have found your lane and maybe even be established in that when you turn 30. And here I was, wanting to change lanes again.

To me, none of this mattered. All I wanted was to realize my true potential and achieve great things. But the way our society is wired, it can have an impact on you. It can play mind games with you. How are you going to spend more time in university without earning money? When are you buying a house? A car? When are you getting married?

I didn’t have any answers to those questions. I still don’t. Because long ago I have decided that I don’t want to explain my answers to anyone, because nobody actually wants to hear. They dont care. Mostly the reason people ask those questions because they want to bring you down. They know you are not ready to get married yet, so they keep asking the same. They know you don’t have the money to buy a car yet, so they keep reminding you that this person or that person bought this car, bought a two story house bla bla bla.

Don’t get me wrong, I do appreciate the people who has achieved materialistic success in their lives. That too is an achievement. They have been persistent, worked hard, managed their finances well and invested in property. People who get married young, they have invested their time and trust into another person and decided to build a family together. That too takes courage.

Now in my 30s, I wanted to switch gears again and get into data science. There were two reasons behind this. Firstly, I felt like what I was currently doing wans’t challenging me enough. I wanted more. I wanted to do things that will change the world. I wanted to shoot for the stars. Secondly, as a child I was fascinated by astronomy. I still am. But the way things went in my life, a few mistakes and some bad decisions later, I found myself running after the same thing everyone else was doing in my early 20s. I was following the trend. It was trendy at the time to become a software engineer. So I became one. I did end up liking the tech industry, so that was okay. Later I realized I don’t wanna sit in a chair coding all day. SO I switched to Business Analysis. As I matured, I started discovering more about myself which was into the late 20s. Now the reason I spoke about astronomy is, when i turned 30 I realized that maybe I should pursue my dream now. So I wanted to combine my skills in IT with my life long passion in astronomy. How can I do that?

I learned that space agencies rely a lot on data. Their missions, rovers and satellites collect vast amounts of data and it is paramount that the data is being used properly to make sense out of it. One thing that really peaked my interest was when I read how important data science was in identifying near earth asteroids and to determine if their path crosses with Earth’s. I fascinated me to think that scientists working with data can predict a future event like that and potentially save our planet from destruction. That sounded so cool to me.

So I researched about data science a lot. I realized that here is a field where I can leverage my current skills and achieve something. Data scientists require programming skills. I had programming knowledge from my undergraduate and initial work experience that I could use here. Also data scientists or analysis require good presentation and analytical skills to visualize their data, present their findings to a larger audience. As a business analyst, I have honed my communication, presentation and people skills which I can leverage here. That’s when I realized here is something I can do while taking full advantage of what I have learned or practiced so far. I didn’t have to completely forget about my previous education or experience.

While all of this was going on, I was in a really bad place in my life. I wasn’t happy with work, I wasn’t happy with the way my life was going in general which is due to a lot of reasons which I’m not going to bore you with. So I decided to take a year off, and reset.

First thing I wanted to do was to get a formal education in the field. My postgraduate was long overdue so I thought why not do my masters in data science. I researched a lot of universities and applied to the ones I thought to be the best fit for my situation and what I wanted to learn. This was around January and February so I ended up applying for the fall semester. Now I had about 6 months until I got a decision from a university and actually starting my studies.

I decided to utilize this 6 months to learn. Learn the skills required for a data scientist. After watching several YouTube videos and reading a few articles, I came up with this chart. Apologies for the typos :)

Now I’m not claiming this is an exclusive list of skills needed for a data scientists. There are tons more. But this is what I initially set out to accomplish in 6 months. I also found this image on the internet which I thought was nice.

I thought that I can start here, when I learn more I can expand this chart later. I did more research and created a syllabus for myself. I’m going to share that here, hopefully it can help at least one more person to learn.

By the time I’m publishing this article, I’m one month into my journey and I think I have made good progress because I have finished foundations of math, excel, git and SQL lessons. Now this syllabus is not complete yet as I keep learning as I progress and discovering more aspects of data science and honestly I have little to no idea about some topics. In my next article I will talk about my journey so far, the challenges and whether I actually enjoyed learning.