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nurulislam135   , 18

from New Marlborough


With the internet being made cheaper and readily available to almost every person in the world, the statement – “The world grows smaller day by day” gets proved substantially right with every passing second. Such a rapid growth in the scaling of the telecom industry and technology has made the internet a basic amenity for humans apart from food, clothing, and shelter.


The biggest consequence of readily available internet to the masses has resulted in the creation of mountain-loads of data- that can be structured, unstructured or even semi-structured. Furthermore, in a world that is heavily reliant on customized and tailor-made outputs and final products for every individual, a whole new field of study came up to derive patterns and logical sequences and continuances in a set of a completely random and haphazard heap of data. A field that has evolved to be known as DATA SCIENCE. A field that makes use of the numerous patterns and similarities existing in a massive data pool and then derive conclusions, correlations, and other parameters depending upon the business logic and the requirements.


As the study of data science increased, the need for more powerful machines emerged which gave not a rise but actually a jumpstart to two already existing fields of study named machine learning and artificial intelligence which have grown to be one of the most important and a backbone of a countless number of industries.

What makes both these fields so vital is their ability to learn from past experience themselves without any actual human intervention. What is needed is just the random and huge volumes of data discussed and these technologies start sorting and making sense of the data in accordance with the algorithm or requirements fed into them. The quality and variety of the data determine the tuning and precision of the machines. All that hard work of creating those complex algorithms will be down the drain if there is no quality data to give as input.

As such, a vast number of machine learning algorithms and artificial intelligences have come up such as Siri, OKGoogle in case of artificial intelligences and supervised and unsupervised learning algorithms in case of machine learning used mostly by companies dealing with big data and wanting to extrapolate that data and develop algorithms to make some daily work easier.



As simple and easy it may sound, but analytical and critical thinking to bring order out of chaos is not a Childs’ play at all. Had it been that easy, the biggest of companies won’t be just throwing around money like anything just to get their hands on a proper data scientist who packs the potential to not just interpret and play with copious amounts of data, but also deliver proper and efficient results on time. The biggest reason to choose the field of data science right now at the moment is due to literally no competition in this field in the market. With very few people who can actually think their way around an unsorted mess, and the supply for the same matching nowhere with the demand, people and companies are willing to go out of their way and budget in order to land someone who can be deemed a proper professional.



The law of demand and supply is not even in regards to the field of data science course. In the present scenario, the supply is significantly smaller than what the market requires. So, in case you want to switch fields or opt for data science, the time to get professional help is now.