Python has recently become one of the most widely used programming languages on the planet. One of the main reasons for this can be its versatile use in different fields of technology. This general-purpose language has been designed for a variety of applications which include data research, software and web development, automation, and simplifying certain daily tasks in general.
Besides its versatility, another reason behind Python’s growing popularity is that it is a user-friendly programming language. Python’s simple and concise syntaxes are very close to actual English, making it easy to read and grasp. This not only makes it popular among new programmers but also speeds up the development of projects as well as the improvement of existing ones.
Furthermore, it’s free to use and distribute, even for commercial reasons, because it’s open-source and has a large online repository of libraries and modules that extends Python’s capabilities.
Now a question arises, which industries use Python? A wide spectrum of industries ranging from web development to finance are now heavily dependent on Python for its high degree of capacity. This has in turn resulted in a massive influx of Python programmers and developers in these industries.
On that note, let’s talk about a few of the top industries that are heavily interested in recruiting skilled coders and developers proficient in Python.
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Data Science
Python has become an integral component of data science, allowing data analysts, data scientists, data engineers and other professionals to manipulate and process data, perform complex statistical and mathematical calculations, generate data visualisations, write algorithms in machine learning and other data-related functions using the language.
Python can be used to create various data visualizations such as graphs, charts, 3D Plots and more. Furthermore, it has a large number of frameworks such as Pytorch and TensorFlow to help coders write codes for the purpose of data analysis and machine learning more productively.
Thanks to these features, there is no doubt that Python is one of the most extensively used programming languages for working with big data.
Due to this development in data science, it is likely more IT jobs will centre around Python in the coming years. You can take a Python programming course by visiting the best learning sites for Python online to add a leading programming language to your skillset.
Web Development and Web Applications
In the recent past, Python has been used by some of the popular platforms for the back-end development of their website or applications. These include Netflix, Dropbox, Spotify and Uber to name a few.
Python when used in web development enables websites and web apps to send, receive, process data, connect with databases, maintain cybersecurity and more. Back-end developer, full-stack developer, software and app developer, DevOps engineers are some web development career prospects that employ Python.
Machine Learning
The field of Machine learning includes artificial intelligence (AI), speech recognition, automated transaction services and others, and Python plays a major role in all these areas under Machine Learning. For example, even the Netflix recommendations you get when you log in is an algorithm written in Python.
Specific machine learning libraries and frameworks such as scikit-learn are used to employ Python.
Fintech
Python dominates other programming languages when it comes to financial technology. However, it was later found out that the use of Python is not only limited to Fintech but is prevalent all across the financial industry.
If you wish to pursue a lucrative software development career in Finance, then it is advised that you learn Python and become a Python developer which is a good place to start.
However, there are multiple learning platforms online and deciding How to learn Python in easy steps can be a difficult task. However, you can go through some genuine online recommendations and reviews that can help you find the right platforms and courses to learn Python.
