The Reason You’re Frustrated when Trying to Become a Data Scientist

The Reason You’re Frustrated when Trying to Become a Data Scientist

The hidden skill that separates the best from the rest

Over-demanding Expectations…

How many times have we seen the post “5 things you need to become a Data Scientist”, “How to become a Data Scientist in 2020”, or the images of the Venn diagrams?

Don’t feel bad if when you read the requirements you curled up into a ball, sucked your thumb and procrastinated even harder on your goals because it’s unlikely you’re alone in this situation. If you are frustrated, its arguably not entirely your fault as to why you are feeling this way.

Data Science is a large field with many cross sections to other disciplines, but I think we have complicated the criteria for becoming a Data Scientist with many complex prerequisites, which are required further down the line, but are not what will keep you going in the long run.

Anyone can become a Data Scientist. It takes is the will to do it and the desire to carry out whatever it takes. Two traits of which every human can realize.

Am I saying that you do not need to know some key topics such as Linear Algebra, Statistics, Calculus, a Programming language – Python and R seem to be the most popular – and heck load of other stuff? Of-course not! To understand the inner workings of Logistic Regression or to dissect a typical research paper, you are probably going to want to know some linear algebra, or statistics or calculus — depending on what paper you are reading — if you want to make it out alive.

What I am saying is that the fundamental skill that is required to become Data Scientist (and to remain one for the long haul) is not Data Visualization, understanding Machine Learning algorithms, or all the others that we I’ve already listed, and those that we have been told that I have not added. Instead, the fundamental skill is the ability to learn, quickly!

“The illiterate of the 21st century will not be those that cannot read and write, but those who cannot learn, unlearn and relearn” — Alvin Toffler

I have written a story about the 3 stages of Learning Data Science that discusses the process of learning which, when understood, can boost how fast you learn.

Defining the terms

Learning is the process of acquiring new understanding, knowledge, behaviors, skills, values attitudes or preferences. We regard someone to be a good learner when they are consistently updating the aforementioned things effectively in a manner that betters their well-being.

Data Science is an inter-disciplinary field that uses scientific methods, processes, algorithms and systems to extract knowledge and insights from many structural and unstructured data (source: Wikipedia ). An effective Data Scientist is consistently capable enforcing techniques that constantly allows them to extract knowledge and insights that could be used to solve real world problems.