The demand for data scientists in all industries is growing rapidly and everyone desperately needs them today to handle large data sets and extract valuable insights from that data. This is because we are living in an age of modern technology where data is considered a new oil.
Today, there are approximately 4.66 billion active Internet users worldwide, of which 700 million are in India alone and billions of data are being generated from them.
In order to stay competitive in the market, every company needs to find important patterns, trends, and information from such a large amount of data.
And all these needs have made the data scientist’s career a very lucrative one and have created 1.5 lakh job opportunities in India alone, which is 62% more than in previous years.
But this field is not for everyone, but only for those who have good command in both the right tools and the perfect set of skills.
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In which programming languages play a more important role in the field of data science. This is why every data scientist requires coding not only to create machine learning models and algorithms but also to collect, extract and handle data more accurately and quickly.
Now you know that data scientists require coding but do you know what is the role of coding in data science and which programming languages are in demand and mostly used by data scientists.
If not, then keep reading, because here we are going to share with you the importance of coding and a brief overview of the most important and widely used programming languages in 2021.
Let’s get started!
What Is the Importance of Coding in Data Science?
To produce accurate results and do data analysis, machine learning algorithms and models are used and programming here helps us to communicate with machines.
Having command in some of the best programming languages is a great skill because most interviewers want to see if a particular candidate can solve problems related to database and data handling using coding or not.
Programming languages are also very important for learning different data science functions and extracting data from different sources and storing it in the database.
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As a data scientist, anyone needs to clear data and delete any unwanted, duplicates files, which also requires coding.
Not only that, coding is everywhere in data science, and knowing some of the best programming languages can help you in getting a good job.
4 Must-Know Programming Languages for Data Scientist
Now is the time to find out what programming languages you need to learn if you are considering pursuing a career as a data scientist.
So, here is a list of some of the best programming languages:
Python
Yes, Python is one of the first programming languages you need to learn to pursue a career as a data scientist.
It is one of the most popular coding languages and you will find it at the top of every list because of its simplicity and large support community.
It is growing rapidly as it is very easy to learn, use and write codes. It is an open-source and general-purpose language that provides many great packages for data scientists.
R
After Python, R is the most widely used tool for statistical computing and data analysis that comes with approximately 10,000 packages.
It is also an open-source language that helps data scientists in data cleaning, data handling, analysis, representation, data visualization, and much more.
R Libraries make it much easier for data scientists to analyze with more detail and accessibility.
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Julia
Due to the rapid execution of complex and large data sets, Julia is rapidly gaining popularity among data scientists.
It is a high-level dynamic coding language that is really helpful in implementing mathematical concepts speedily.
It is only 10 years since its release, but it is growing very fast because of its ease of handling metrics, and its irreplaceable advantages in numerical analysis.
SQL
After collecting data from different sources, the next big task is to manage it and this is where SQL (Structured Query Language) is used for storing and retrieving data.
This is a very popular programming language that is used for database management systems and large databases.
If you know how to store, manipulate and retrieve data in a relative database using SQL, then this can prove to be a huge asset to you in the field of data science.
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