Learning About Data

23rd March 2020 in Portfolio

What Did I Learn?

The core principle of data analytics is distinguishing signal from noise. There are 2 parts to this:

  1. Discovering signals
  2. Knowing which signals are meaningful

The user flow below is just one example of signal discovery.

I was also excited to apply this knowledge to build a churn prediction model at TradeGecko.

Visualizing User Onboarding Patterns

To look at data in different ways and come up with new insights, requires a toolkit that is both broad and deep.

I spent countless hours outside work going through statistics textbooks, online courses, and exploring data.

Most Popular Textbooks On Data

As a Sociology major, this knowledge was completely alien to me.

So I took up a full 10 course specialization in Data Science that was offered by John Hopkins University.

John Hopkins Data Science Specialization

Then there are the tools. If you get a kick from learning new things, try going into data analytics; it will be a playground.

Data Analytics Programming Languages

Why Did I Learn It?

In university, my coursework was mainly focused on making meaning from qualitative insights (small data).

Been curious about the grass on the other side of the fence, I took up a statistics class during my graduating year.

This sparked my curiosity in understanding patterns from bigger datasets and before you know it, I was learning computer science from Scratch (yes, the cat)

Scratch Programming

Keen To Learn More?

If you want to hear more about this story and where it has led me, drop me a message below๐Ÿ‘‡