Have you ever developed an interest in data science and thought of becoming a data scientist?
Do you know according to a report by Forbes, Data science is ranked the best tech job in 2021? Moreover, it is at a constant spot for 3 years.
As we all know, businesses are constantly generating huge amounts of data. And so the demand for data science scientists is raising day by day.
But if you are looking towards a career in data science, you need to be thorough with both programming languages and mathematical skills. To be able to access and analyze the gathered data, a person needs the best data science skills and tools.
In this article, we will share the most desired programming language required to achieve a career in data science.
Python was created by Guido Van Rossum in the year 1991. It is a high-level language that is object-oriented. It is considered one of the most popular languages for data science. Python is used by more than 50 % of data scientists.
Now the question arises why is python so frequently used?
It is because it is easy to learn and contains around a ton of really useful libraries used for deriving value from data. And so, it is considered convenient by many.
Some of the really easy and helpful python libraries from a data science perspective are Pandas, NumPy, Matplotlib etc.
There is n number of online tutorials available online that can give you a brief idea about python and how to work with python.
The next programming language on our list is R. It is an open-source, object-oriented programming language. It is widely used for statistical computing and graphics.
Although you can consider R as one of the most desirable programming languages for data science in 2021, the learning curve of R programming is comparatively steep compared to python.
R contains a lappy function, which is able to perform high iteration operations that too faster than python.
Let’s move forward towards the next programming language on our list.
SQL, commonly known as Structured Query Language, is a programming language for creating, reading, updating, and deleting data in relational databases such as MySQL, SQLite, and Microsoft SQL Server.
It is the most popular language widely used for updating, querying and manipulating databases by data scientists.
Most of the data science recruiters require skills in SQL. But thank god! it is really easy to learn because of its really high readable syntax.
Scala, also known as scalable language is an open-source multi- paradigm concurrent programming language. It was developed in the year, 2003 by Martin Odersky.
It is known as one of the most stable, fast, flexible and scalable programming languages. This is the reason why it is known as one of the feasible and popular languages for data science.
If a person is looking for doing machine learning at a large scale or building complex high-level algorithms then Scala is what you are looking for.
Do check our blog on, How to get started with machine learning? Click here
The next one on our list is Julia.
Julia was created by a group of computer scientists and MIT mathematicians. Since then Julia has really achieved popularity in the field of data science and machine learning.
Julia is basically a modern and high-performance programming language. It is open-source and mostly used for data manipulations in addition to scientific calculation.
Moreover, it is known for its ability to solve complex mathematical operations and that too at a really high speed.
It is 30x faster when compared to python when it comes to handling data. This is the reason why we consider it as one of the most desirable programming languages for data science.
Let’s move forward and check the next programming language on our list.
Yes, we know it doesn’t actually appear to be an obvious language but it is. It is one of the best programming languages for data science and the credit goes to data science frameworks like Hadoop which runs on JVM.
Java is basically a general-purpose cross-platform object-oriented programming language. It is widely used in web, desktop, mobile and embedded applications.
Java also contains a variety of libraries and tools that are really essential for machine learning and data science.
The next programming language on our list is Matlab. Matlab stands for matrix laboratory. It is a multi-paradigm numerical computing language. Mathworks developed it with the motive of using it in numerical computations.
Fourier transforms, signal processing, image processing, and matrix algebra are just a few of its fascinating uses.
Matlab is a must-learn skill for anyone serious about a career in data science, even if it is less popular than Python.
Last but not the least, C and C++ provide exceptional capabilities for the development of statistics and data tools.
C/C++ is also surprising beneficial because it swiftly compiles data. It creates highly functional tools that can be fine-tuned to perfection.
But if you are new to programming languages, it can give you a tough time.
So, these were 8 programming languages that we consider the best when it comes to data science.