Why You Should Learn Python
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Not only was Python popular among respondents, it was also well-loved. It was the second-most loved programming language, only trailing Rust, in Stack Overflow’s Survey. For respondents, it was the most wanted programming language. That means that developers who aren’t using Python in their day-to-day want to use the programming language.
The reason for its rising popularity is because developers are constantly finding new ways to use Python. This is especially true in data science.
Python is a powerful language, much to the delight of developers and data scientists. If you’re interested in machine learning or data analytics, you’ll need to learn Python, according to Dice. Being able to organize and analyze a massive amount of data efficiently is crucial for any company’s success and Python does just that.
For example, Netflix uses Python within its data science team. According to the Netflix TechBlog, it’s used to:
“Help surface insights from the vast quantities of data produced by the organization. Python is used in tools for monitoring data quality, managing data movement and syncing, expressing business logic inside our ETL workflows, and running various web applications to visualize data.”
The streaming giant also uses Python for developing applications internally.
It’s relatively easy to use
Based on its rapid adoption and popularity, you might have guessed that Python was an easy programming language to learn. You’d be right with the natural caveat that learning anything new requires patience and effort on your end.
That being said, Python rewards you for your investment. For starters, it’s quite easy to get started with because of less complex syntax when compared to other programming languages, according to KDnuggets. Python also has great resources for beginners and for programmers/data scientists who want to learn the language.
Our free Data Science Bootcamp Prep is another great resource to try your hand at Python. Over the course of 75+ hours, you’ll gain first-hand knowledge of data science basics, Python, machine learning, and math fundamentals.
Posted by Charles Poladian / October 17, 2019
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