Why do we learn Python?
The world has witnessed the emergence of a large number of programming languages such as: (JAVA), (C) or (C), or (C++) or (C++), or (C Sharp) C#, or (JavaScript) JavaScript or (Python). Python, from 1950 until now, every language is designed to serve a purpose.
As a result, many great software applications have been developed, and many complex problems in our world have been solved. With the speed of development, the search for a more powerful language began. Some ancient languages were able to continue to evolve and reach the world we know today, while some have disappeared.
Moreover, new technologies and digitization have dominated our world today, which helped to extract a lot of data, which many companies seek to process and analyze; To be used for a wide range of purposes such as: designing applications, providing new services, and predicting consumer behavior in a better way.
Therefore, a large group of new emerging jobs have emerged that require proficiency in programming languages, and one of these jobs is the Data Scientist job, which is needed by many companies and organizations today.
Here, an important question arises, why is learning the programming language (Python) necessary for a career in data science?
With the advancement of new technologies such as: machine learning, artificial intelligence, and predictive analytics, data science is gaining more importance every day. So it has become a popular career choice among people.
Data scientists point out that getting and sorting data makes up 80% of their work, as data can be messy, have missing or irrational values, or have no consistent records, although there are many tools and programming languages that help with this. However, Python is the most preferred language for many reasons, including:
1- Versatile programming language:
Developers and researchers use Python in many areas, such as: application development, training of machine learning and deep learning models, natural language processing, image recognition, data analysis and processing, and there is no other language so far that is better than it at all.
Reports indicate that Python is officially the most widely used programming language in the world today, beating Java, which has been the language of choice for developers around the world for the longest period of time. But the dynamic nature of Python, its inclusion of multiple libraries with built-in features for just about everything, has made it a popular choice among developers and researchers.
2- Open source language:
One of the best features of Python is that it is an open source and scalable programming language, which means that anyone can add new functionality to their existing ones, and in fact every day companies offer their own set of frameworks and functions that help them achieve their goals faster.
3- Easy to learn:
Python is a programming language that is very easy to learn and start projects with when compared to other data science languages like: R and MATLAB.
Whether you are a beginner planning to start your career in data science, or a seasoned professional who is developing new skills, you can learn them easily without investing a lot of time and resources into it.
4- Adaptable:
Python allows developers and data scientists to approach any problem in many ways rather than just sticking to one particular approach, which helps them come up with effective solutions easily. Therefore, YouTube chose to rely on it in the recent period to provide more features to its customers, as well as Dropbox.
In addition, it includes a lot of data science libraries that make it easier to perform the tasks of data scientists, such as: Numpy, Scipy, StatsModels, sci-kit-learn, and it continues to add new libraries to its suite, so data scientists find it a powerful programming language that meets their needs and help them solve problems that were previously unsolvable.