5 Reasons you should not become a Data Scientist!

1) Love for Data: As the name suggests its Data. A data scientist actually loves data. We are not trying to exaggerate this point, but yes you cannot expect to become a Scientist until you love it. The same holds for Data, A data scientist actually dreams numbers and patterns. We don’t mean to say that you should be extremely good at mathematics and your calculation speed should be of the speed of light. But you should have this eternal love for patterns and numbers.

2) Lack of proper background: To become a data scientist you need to understand the core concepts of Machine Learning and after that dig deep into Deep Learning. Only after that you would understand what you are doing. A majority of Data Science Aspirants don’t really know what they are dong. Most of them are in the fantasy land of the salary they will be earning after becoming a Data Scientist. We will have to spell it out for you that it is only after the understanding Machine Learning and Deep Learning that you get a fair idea of how to become one.

3) Data Engineering is not Data Science: Running some big queries on huge distributed clusters is not Data Science. Getting hands on experience in SQL and Data Query languages does not advocate that you know or implement Data Science in anyway.

4) Huge Cost of False Positives and true negatives: You mess up in your models; you pay a huge price for it. Being a Data Scientist requires an Apex level expertise and hands on experience on Data Modeling, slicing and various other aspects of Data. There is really no Data Scientist Fantasy left if you mess up your Data models. On the contrary you pay a huge price for it.

5) Lack of proper Training: A lot of centers are providing courses in Data Science are themselves not equipped enough. The instructor needs to have a background in Math/Statistics/Machine Learning, we are not being country biased here but frankly the strength of people who have an experience in such a fields is fairly scarce. This only leaves these fake data courses to impart incomplete and bogus knowledge.

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