HOW TO PREPARE FOR A CAREER IN DATA SCIENCE?

18Feb - by aiuniverse - 0 - In Data Science

Source: analyticsinsight.net

The continuous advancements in technology and the increasing use of smart devices are leading tremendous growth in data. Considering reports, more than 2.5 Quintilian bytes of data are generated on a daily basis and it is expected that 1.7 Mb of data will be produced every second in the near future. This is where data scientists play an influential role in analyzing these immense amounts of data to convert into meaningful insights. Data science is an overriding method today that will remain the same for the future. This drives the need for skilled talent across industries to meet the challenges of data analytics and assist delivering innovation in products, services and society.

Many businesses around the world now are looking for data scientists as they receive both structured and unstructured data. Organizations are realizing the need to manage this data to provide greater services to their customers, and this is why the demand for data scientists is accelerating.

Thus, to get started with it, candidates need to start with comprehensive data science courses that can assist them to better prepare for the demands of being a data scientist, while also positioning them to take up the future data science roles.

Here are some technical skills required to drive a career in data science.

Programming

Programming language can help a candidate to clean, assemble, and organize an unstructured set of data. It can also assist in manipulating the data and apply specific algorithms to come up with some meaningful insights. As most languages cater to the development of software, programming for Data Science differs in the sense where it supports users to pre-process, assess and make predictions from the data. Python and R are one of the most used languages by data scientists.

Statistics

A good understanding of statistics is essential as a data scientist. It is a study of the anthology, analysis, presentation, and organization of data. This will also be the case for machine learning, but one of the vital aspects of your statistics knowledge will be understanding when diverse techniques are or aren’t a valid approach. Statistics is imperative across all company types. A data analyst must possess an in-depth understanding of descriptive statistics and probability theory that can be gained through a specialized program.

Machine Learning

By developing accurate machine learning models, a company has a better chance to recognize profitable opportunities and dodge unknown risks. Thus, to build this model requires specific knowledge that can be gained through a specialized data science program or course. Familiarizing with machine learning methods is significant if you are at a large company with vast amounts of data, or working at a company where the product itself is especially data-driven.

Data Science is the Future

Certainly, developing a career in data science is a lucrative one. This will become more popular in years to come as the introduction of data-driven strategies will continue to gain prevalence. The future data scientists would be able to handle the most critical and complex business challenges. They will be able to do this because they would have the knowledge of the right skills and techniques required to bring a change in an organization.

According to reports, India would face a deficiency of data scientists until 2020 as they are required to assess an immense amount of data, make decisions and predictions. So, for all this purpose, they need to have skills in statistics, mathematics, data visualization, machine learning, and coding. As noted by an IBM survey, there will be an increase in job openings of 364,000 to 2,720,000 data scientists in the year 2020.

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