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Advantages of a Data Science Certification?

HomeEducationalAdvantages of a Data Science Certification?

Fueled by technologies like big data and artificial intelligence, the demand for data scientist is growing exponentially. Thanks to the rapid pace in how data is growing at a breakneck speed. Whether you’re a fresh graduate or a working professional or someone looking to upgrade his skills in data science, you must know that your skills will only be marketable by acquiring the skillset employers are looking to hire for today.

Data science was termed as, “The sexiest job of the 21st century” in 2012 and it remains to be one of the most in-demand and popular job today. According to a study by IBM, it is estimated that by 2020 28% of data scientists will grow to meet the industry’s increased demand.

But did you know that we’re still stuck with very low supply of data science professionals? Over 151,000 data scientist jobs remained vacant in the U.S., statistics taken from LinkedIn Workforce Report. Los Angeles, New York, and San Francisco recorded to have acute shortage in data science skills. Although the demand keeps increasing for professionals skilled in data science, the supply remains a challenge.

As data keep increasing, there is a lot of hunting taking place for expert professionals skilled in data science. It is said, better late than sorry. For someone looking to get into data science and wish to remain in sync with the technology market, it is highly recommended to take up data science certification.

Perks of learning from data science certification:

Learn it from the industry based instructors

This is a bit tricky. It is highly advisable for one to learn it through instructors having industry based experience. No candidate would appreciate learning from university professors. Most often teachers and instructors belong from such category. Ensure your mentor or guide has relevant industry experience.

Work with the latest technology skills and stack

Employers look for candidates with the latest technology knowledge. Now whom would you choose, a professor with no industry knowledge or someone with industry knowledge. It is important to stick with those having industry knowledge, gaining the latest experience and skills can keep you ahead of others in the competitive market.

Just stick to essentials

If you’re a data science professional, no one would expect you to derive AI algorithms from the very first principle. With the level of experience, one does not need to dive deep into the history behind every algorithm used. You need to learn what exactly employers are looking from you and get skilled in those technologies.

GitHub for projects

Probably GitHub is one of the best resources from where one can gain practical knowledge. Looking to enhance your programming skills and work with open source projects, then this platform might be the best platform to get those practical skills. Create your portfolio and keep coding, one can perfect programming skills by constant practice through GitHub.

Gain individual attention

In colleges and universities, it often gets challenging to focus on a single individual, however, through credible data science program one gets the opportunity to get their own mentor/instructor. Having your own instructor or mentor to guide you is an added advantage, for every doubt or query the mentor is available to help the student with their query or their doubts.

Data science jobs has been on the hype from the past six years now, fresh graduates and students from computer science background might gain maximum benefit out of it since job opportunities are huge. Data science is still a vibrant field, and in terms of skill set and job perspective it will remain as one of the in-demand career opportunities.

pearls of wisdom
Contributing Author
Contributing Author
InPeaks.com gives you an awesome opportunity to submit your unique content that are educative, informative, knowledgeable and adding value to the people. You may submit the post using the 'Guest Blog' link. Read the guidelines before submission. Thank you.

1 COMMENT

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