Pursue Data Science with a Non-Tech Background

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All our dreams can come true if we have the courage to pursue them.” – Walt Disney

The above statement is one of the most inspiring quotes to read. It’s something that remains deep within anyone’s memory and serves as a reminder to never ever halt any progress or miss a growth opportunity in life. What’s more to this is that one should always stay focused and determined to achieve their goal.

What makes this universe more amazing is the fact that humans have the ability to learn, grasp and understand the complex and sophisticated nature of the environment in order to make their life easy and smooth. Whilst we tried to scrutinize on this ever-doubting subject to give you a simpler understanding – How to get into Data Science from a non-technical background?

It takes great efforts and honesty to reach one’s goals. If one is dedicated and motivated, they can surely achieve the impossible. One just needs to embrace that mentality of getting into data science and continue their career.

Doug Cutting – Chief Architect of Cloudera, one of the most famous data engineers in the world and the creator of the Hadoop framework that helped propel data science into the mainstream graduated with a bachelor’s degree in linguistics. Tim O’Reilly, the founder of O’Reilly Media, and the man who popularized the terms open source and Web 2.0 graduated in Classics.

It evidently doesn’t ask to put in hundreds of hours to understand the technical concepts but to follow a logical and smart approach which can make the job much easier and efficient. It can be an onerous task to become a data scientist, but not an impossible one.

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Anyone can get into data science from a non-technical background and do wonders working on with a simple pathway –

  • First, identify your current skills and which field you would like to pursue.
  • Then, see how relevant and useful the technical or management skills required for your job are.
  • Identify which technical languages and courses are perfectly suited for your job.
  • Work on them through various resources and facilities available at your disposal.
  • Start learning and practising on your own so that you can keep up to your goal.
  • Take the help of professionals who are expert in this domain.
  • Join the course best suited for your role.

Check out these real-life examples of people who made it in Data Science despite their non-technical background.

INSOFE alumni Asif Mohammad, a B.Sc. graduate in Chemistry overcame all challenges and kept his morale high while learning Data Science at INSOFE.

He believed playing with data sets and solving real-world problems was really challenging and robust. With the prodigious support from the mentors and Data Scientists whenever required, made this transition from a non-technical field to data science both hassle-free and interesting for him.  He added, ‘The course structure was designed aptly to impart hands-on experience for what was taught in the theory classes, enhancing the knowledge furthermore in the field through several assignments, examinations and hackathons”.

It is great to see how Asif Mohammad was able to pursue his dream career with sheer hard work and determination. 

Here’s how Mr Sourav Datta’s passion and zeal to learn the technical model of Data Analytics paved a new path for his career.

Mr Sourav Datta, an alumnus of INSOFE shares that it takes a plethora of motivation, commitment and seriousness to invest full weekends towards new learning for a sustained period of time, especially for working-class professionals. He believes those who understand the importance of weekends and invest that again into learning take another bold and courageous decision.

He talks about his accidental journey to Analytics – ‘It was never a plan to move into Analytics as I had minimal knowledge on the technical aspects of Analytics such as Python, R Language, NoSQL and SAAS. I continuously tried to implement my Business expertise to derive Analytical models and solutions so that we can adopt/ use them in our Business Decisions. What I was immensely lacking was the technical knowledge and that was changed completely when I attended the 6 months PGP course at INSOFE. All the classes were extremely productive and useful. It was covering all the fundamental and advanced courses of Data Science and Analytics. This was really helpful for me and today when I sit with my colleagues, I feel confident and empowered giving new ideas and layouts, not just talking something in thin air’. 

Find the data science ‘niche’ you want to specialize in and pursue the training and education for it. There are innumerable courses that give you the necessary theoretical knowledge you need. INSOFE, for one, offers customized programs for corporates whereas the classroom program is conducted over 23 weekends that has more than 184 hours of hands-on lab sessions preparing engineers to embrace advanced technologies through a variety of applications and solve challenging Data Science problems in organizations spanning across industry verticals.

To find out more about our courses, click here.

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