Data scientists are gaining more prominence among major big tech companies than ever before

The 21st century is ruled by data and hence the demand for intelligent data scientists has been on the rise significantly. The domains of data science and machine learning have emerged as the most in-demand skills in the tech industry, but constant upskilling and specialization are also utterly important because the tech landscape is constantly evolving. The actual focus for tech aspirants lies in garnering the critical data science skills that are critical to be employable and excel in this profession. Enterprises are busy leveraging the utility of big data to generate insights that drive demand for data scientists across industry verticals at all enterprise skills. Coming to the scenario in India, data science has become equally important for Indian companies, hence, the demand for data scientists has grown impeccably over the past couple of years.

Understanding the basics of data science has become essential. However, as the popularity of data science grew, more and more professionals from different career paths have chosen to shift to data science, here is why the number of self-taught data scientists is rising significantly. The field of data science is full of potential and opportunities, and also offers lucrative financial packages. This is one of the major triggers why more and more self-taught data scientists are joining the ecosystem. In a nutshell, aspirations for being a data scientist have grown among tech professionals. However, the craze does not only stop at acquiring a data science career, several aspirants choose to learn data science skills to add value to their present roles, and gain an edge over the growing competition.

So, How do You Establish Yourself as Self-Taught Data Science in India?

Well, the answer to this question is pretty simple. The rules for gaining a foothold in the data science industry in India are quite similar to the ones in the global industry. To excel in this field an aspiring data scientist should primarily focus on deciding on a specialization. However, the difficulty of learning data science vastly depends on one's background. Just like learning human languages, having an existing background in computer science and mathematics will help candidates take a leap in the self-learning process.

There are also several non-traditional approaches to learning data science, including online data science courses and programs, available on websites like edX, Coursera, and Udemy, to name a few. These online courses offer flexibility to the candidates. Besides, data science experts believe that the domain is about gaining practical years. Hence, candidates can initially start by downloading programs that explain programming languages, the different data science frameworks, and the tools that professionals use to gain insights from large datasets. Data scientists have to constantly explore the different resources that are available to gain proper knowledge about this evolving ecosystem.

Bottom Line

As mentioned earlier, to become a successful data scientist, upskilling, re-learning, or unlearning is quite important. The field has become a trend for aspiring tech professionals, it might be difficult and scary for self-learning data science aspirants, but determination and courage will help them go a long way. In fact, based on reports, several major big tech companies across the world are preferring to hire self-taught data scientists over college or university-graduated data professionals. It is mainly due to their courage and motivation to learn something completely new that is exciting modern business leaders to hire more self-taught data scientists.