Data science is the buzzword that has gripped the entire world. Despite of its ever-growing popularity, there are many questions related to this field. This article aims to remove your doubts related to this course.

What is data science?

Data science can be simply explained as a blend of various algorithms, mathematical concepts and tools to discover some interesting and hidden patterns from raw data. In today’s world, almost all the companies make use of it to find hidden patterns that help companies make informed decisions.

Why the hype around data science?

The main reason for a lot of hype is because of the kind of salary which such a job profile fetches. It can fetch you a really good salary. A junior data scientist can get a salary of INR 4 to 6 lacs and experienced data scientists’ salary can range from INR 6 lacs to 12 lacs and more. It also provides job security, because nowadays every company needs a data scientist. And the applications are also myriad. It is not just restricted to a single domain. It has applications in fields like finance, e-commerce, healthcare, agriculture, social media, entertainment and many more fields. Its applications are truly endless.

How to become a data scientist?

The answer to this question is as simple as the question itself. To become a data scientist, an interested person has to take up a course in data science, Complete the course and obtain a certificate. The course can be taken up easily on online platforms, there are paid as well as unpaid course available or else you can go to coaching classes. Even some premium institutes offer courses. You can even self-tutor yourself. Yes, that is absolutely possible, if you are sincere enough. These days, with internet accessible to everyone, a lot of relevant resources can be found and they can be studied well. An engineering or science background is necessary to become a data scientist. Moreover a solid base in mathematics, coding and data mining will help you to grasp the technicalities well.

Some data science jargons:

Discovery of data science insights:

It deals with finding interesting patterns from the data, by going to the grassroots level of data to mine and understand its behavior and trends. The whole process of discovery of data insights start with data exploration and then understanding the data patterns and then applying some relevant techniques to produce the desired results. Data insights give some clarity and are also helpful in providing good business strategies.

Development of data products:

It primarily involves two steps, one is using data as input and the second is to process that data to produce results. A simple example of this could be an engine that provides recommendation based on the inputs.

Through this article we have tried to cover most of the topics related to data science.

Source by Shalini M