Why is it Essential for Data Scientists to Learn Python?

Analytics Insight explains the reasons for data scientists to learn Python at the beginning

Python has become one of the most essential and high-level programming languages in Data Science in these recent years. Reputed organizations want data scientists to have a clear understanding of coding with Python through the most important Python libraries available on the internet such as TensorFlow, NumPy, and Pandas. Data scientists can learn Python to grab the best job opportunities with lucrative salary packages across the world. Thus, let's explore why it is essential for data scientists to learn Python before joining any company.

Python is thriving as an open-source programming language in the groups of data scientists and developers, besides Java, C++, R, and so on across the world. It is because Python in Data Science supports object-oriented, structures, as well as a functional programming paradigm. This programming language is designed to be readable, simple, and explainable for completing multiple tasks. Data scientists have a Bachelor's or Master's degree from any technical field such as statistics, mathematics, computer science, and so on. Some of them do not have sufficient coding skills to enter the field of Data Science. Thus, Python syntax has become easy to code and data scientists can learn Python in Data Science as fast as possible.

As mentioned above, there is an emergence of multiple free or paid resources to get a grip and understanding of Python to work in Data Science at a comfortable pace. Aspiring data scientists can join the powerful and professional data scientists' community or the Python community to receive education regarding Python in Data Science. Professional websites such as Coursera, Udemy, LinkedIn, Simplilearn, and many more have realized the demand from data scientists for Python courses. So these websites offer multiple online courses at a budget-friendly price with valid and useful certificates to add to the CV for a successful future in Data Science.

Data scientists prefer Python over other languages owing to its availability of powerful machine learning libraries for any robust machine learning algorithms without sacrificing the existing performances. Data scientists can build appropriate neural networks with these powerful frameworks. Dropbox, Google, YouTube, and Instagram are built on Python. It helps in automating multiple tasks as well as the usage of those applications in different kinds of languages with straightforward code and broad documentation.

Since data scientists are required for effective data management, Python is the first language to work with enormous volumes of complex real-time data through multiple data mining tools. Python controls different prominent websites through web development frameworks such as Django, TurboGears, and many more. Data scientists need to be proficient in data analysis with multiple data analytics tools and Python offers better knowledge and correlates real-time data from large datasets with self-service analytics.

It is speculated that the Python package software market can expect a huge demand and growth by 2025 in the field of Data Science whereas the global market growth of Data Science is expected to hit US$140.9 billion by 2024 with a CAGR of 30%. Thus, Python for Data Science can be seen as the most trending and high-demand combination in the tech-driven world from the strong community of data scientists.