Before we begin, a disclaimer – the views expressed in my article are solely my own and are derived from my internal values. You do not have to feel the same way or even agree with me, but I do hope that you are respectful and accepting.
In continuation to the previous blog, I will go through a few steps for someone willing to try out data science and a few of my learnings. However, before we begin, I want to clarify one thing – I have just started my journey and am still in the process of finding my break, I am no expert, and this is just my opinion.
Okay – how I did this. I started looking into data science about a little more than a year ago and read a few blogs about it. I narrowed down on the fundamental tools and knowledge base required. I did an online course and jumped into a diploma. Now let us sketch it out in a few steps:
- Read up on what Data Science is – medium and towards data science are great websites for this
- Get enrolled in MOOC course for Data Science – I took this course from Udemy
- Do a little research and self-learning – I follow this page on YouTube
- Download anaconda – Python distribution platform, it has python and jupyter – your partners for now and all required libraries such as matplotlib, numpy, pandas etc
- Look at websites like Kaggle and this github repo for public datasets
- Get your hands dirty – do a few small/huge projects depending on your appetite
- Remember stackoverflow is your best friend!!!
This was a small and quick sketch, oh and by far it is not all inclusive. In fact I think we didn’t even scratch the surface. So, have fun, be inquisitive and don’t be scared to get your hands dirty! What you learn by practice, you cannot learn any other way.
As always, for further questions reach out to me on LinkedIn.