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Using Python for data science: What you need to know

Using Python for data science: What you need to know


Today, the amount of data that we have at our disposal is overwhelming. Which means the role of data science is more critical than ever. 

“Data science is the art of making sense of data, in an increasingly data-saturated world,” says Michael Berthold, CEO and co-founder of data science company, KNIME. It can also be a rewarding career path, with a high pay floor and plenty of opportunity for growth. 

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If you’re considering a data science career, one programming language you may want to learn is Python. Its combination of powerful libraries, ease of use, community support, and adaptability make Python an indispensable tool for data scientists. Interested in learning more? Here’s what you need to know about using Python for data science.

What is data science?

Data science is a multidisciplinary field that attempts to garner meaningful and actionable learning from complex data. It combines aspects of statistics, computer science, AI, and more. “Data scientists use scientific methods, algorithms, processes, and systems to extract insights and knowledge from data,” explains Justice Erolin, CTO at software development company, BairesDev. Often, the goal of data science is to inform decision-making and strategic planning for businesses.

Pursuing a career in data science can be quite lucrative. The average data scientist salary in the U.S. is $145,257, according to Salary.com, with the salary range typically falling between $130,842 and $159,732. Of course, actual salaries for data scientist…

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