Learning About Data23rd 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:
- Discovering signals
- 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.
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.
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.
Then there are the tools. If you get a kick from learning new things, try going into data analytics; it will be a playground.
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)
Keen To Learn More?
If you want to hear more about this story and where it has led me, drop me a message below👇