An action plan from a Data Scientist to become a Data Scientist in 202X
I am a Mechanical engineer by education. And I started my career with a core job in the steel industry.
With those heavy steel enforced gumboots and that plastic helmet, venturing around big blast furnaces and rolling mills. Artificial safety measures, to say the least, as I knew that nothing would save me if something untoward happens. Maybe some running shoes would have helped. As for the helmet. I would just say that molten steel burns at 1370 degrees C.
As I realized based on my constant fear, that job was not for me, and so I made it my goal to move into the Analytics and Data Science space somewhere around in 2011. From that time, MOOCs have been my goto option for learning new things, and I ended up taking a lot of them. Good ones and bad ones.
Now in 2020, with the Data Science field changing so rapidly, there is no shortage of resources to learn data science. But that also often poses a problem for a beginner as to where to start learning and what to learn? There are a lot of great resources on the internet, but that means there are a lot of bad ones too.
A lot of choices may often result in stagnation as anxiety is not good when it comes to learning.
In his book, The Paradox of Choice — Why More Is Less, Schwartz argues that eliminating consumer choices can greatly reduce anxiety for shoppers. And the same remains true for Data Science courses as well.
This post is about providing recommendations to lost souls with a lot of choices on where to start their Data Science Journey.