The field of data science is opening up for people from an increased variety of backgrounds. This post is primarily targeted towards aspirants whose obvious career path could have been something else.

Data science as a field is not exclusive to experts of computer science and statistics; sure, people from these backgrounds have a clear advantage in some aspects of the field but notice how I refer to data science as a field and not a job. It is a deep discipline with numerous wings and variegated possibilities – there may be a perfect fit waiting for you without even your knowledge. To learn more about the data science field you can check out Projectpro Data science Project.

The last paragraph was dedicated to convincing you that you can become a part of the field of data science regardless of your background. 

Step 1 : Self analysis   

This is a two part process. The first part involves a little self introspection. Ask yourself two simple questions. 

Why do you want to build a career in data science?

Does data science excite you enough to warrant all the research, education, and hands-on training that lies ahead of you?

Once you have clear positive answers to these questions, you can move to the next step. 

Step 2 : Studying the field

My friend Amit is a digital marketer. He had an experience of five odd years in digital marketing and content creation. Now, he builds code bases in Python for data science for instructional blog posts – not the most obvious career move for Amit, but he has learnt his way up and is earning a sizable cheque.

Amit’s story further promotes our initial notion – data science is not an exclusive discipline; you just have to find your place and build the right skills to solidify it. At the end of the day it is not always about being called a data scientist, well, at least not for everyone.

Study the discipline. Understand every aspect of it – industrial, educational, topical. Make sure you move beyond the adverts and search the nooks and corners of the discipline to find a good starting point.

Step 3 : Talk to people

This is a very underrated part of the career building process. And I am not referring to the networking aspect of the job search; this is about communicating with the inside people to gain insights on the field.

Join forums, be a fly in the wall on discussions, find a person who seems approachable and lay down your questions. Tell them what you have been upto and what your aspiration is. One in ten people is likely to come up with some career defining suggestion. If not, it is still worth a try.

Step 4 : Get trained

If you have pursued the first three steps you would by now have a fair idea of what to learn first. In most cases, for non-programmers, learning Python for data science is a popular foot ahead. Depending on your goals you can choose an entry level big data analytics course. The more you study, the more new spaces will present themselves to you.