Last Updated on by Kumar Raja

Common Myths About Career In Data Science

Data Science is a field which is in existence from a long time & has been continuously evolving. Over the past decade, the outbreak of Big Data revolution has led to the outbreak of a colossal demand for Data Science & its relevant technologies like AI & Machine Learning.

Mastering the skills in Data Science would be quite challenging. Data Science showcases superior abilities like computing, scalable storage abilities, predictive modeling with Machine Learning algorithms and more, Having intense knowledge of Data Science, it will be possible to develop new paradigms and can explore many new ways to solve the given problem. Shape your analytics career in Data Science to perfection by joining for the best Data Science Training In Hyderabad program by Kelly Technologies.

Now, let’s have a look at some of the common myths about career in Data Science

It Is Mandatory To Have PhD In Data Science-

PhD isn’t necessary to excel in career as a Data Scientist. However, having PhD in Statistics or Mathematics will surely be an added advantage in Data Science.

If the aspirants are having sound knowledge of data and business understanding & if they can develop intense skills in Stats, R, Python, MapReduce, Spark, Data Visualization & Machine Learning skills then one can easily excel in their career as a Data Scientist without any PhD.

Your Previous Work Experience Will Get Added In Data Science=

If you are having many of years experience in your current industry, then bringing all this experience into Data Science will not be possible. There are two ways in which you can get started building your career in Data Science. You either completely change your domain or you will find the Data Science job role while still working in your existing domain. In the first case, your previous experience will not get added to your Data Science profile.

So if you are having many years of experience then the safest option would be to stay in the same field and then work towards understanding how Data Science can be applied.

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