The buzz around data science reached a crescendo in the past few years. Everybody's talking about it, businesses are craving its experts, and its applications are ever-expanding. As a result, people are flocking to data science and jumping right in by enrolling in courses on data science with professional certificates & coding classes.
But, given the heavy technicality of the domain, is data science a good career choice for everyone?
Can Everyone Become A Data Scientist?
It is only later that many realise that the domain is not a cakewalk. Data science has its roots in pure & applied mathematics, and no matter what the application, engineers NEED to possess strong math, stat & problem-solving skills. So, before you enrol in data science college programs or free online courses, you must ensure you are ready for all the myriad challenges.
Data science is all about implementing statistical methods to analyse and discover knowledge from datasets. Without a solid foundation, you will not be able to progress much further.
Crack programming skills are another essentiality. Some of today's most prominent programming languages, such as R, Python, Golang, etc., are used to design mining & analytics algorithms.
Machine learning and data science can be thought of as two sides of the same coin. Most data science systems employ machine learning & AI in some form or the other, and engineers must have good ideas about potent ML algorithms, natural language processing, deep learning, neural networks, etc.
Besides the above, capable data science professionals need exceptional soft skills such as teamwork, communication, emotional intelligence, etc.
The above skills & ideas are not just necessary but critical. Therefore, a data science professional must sharpen these skills and develop these ideas to the best of their capabilities.
Most venture into the world of data science for the fat paycheck and all the tech savviness. However, the reality is quite different. The job of a data science engineer entails quite a few less exciting & near-mundane tasks, alongside team & pitch meetings, writing & documenting, handling administrative overhead by repeatedly explaining the basics of your model & technique, etc.
Another major misconception of novice data science engineers is the trap of infinite timescale & infinite budget. As a result, they tend to forget time & budget constraints and struggle when circumstances become challenging.
Everything is not for everyone. Before dwelling into the world of data science, please go through this article and think hard about whether you have what it takes. If you do, start with a data science professional certificate course from a reputed platform.
All the best!
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