Any novice computer programmer would have heard about Python, by now. Python has been soaring high in the past couple of years, partly because of its uses and partly because of its usability. It is currently the second most popular programming language in the world. Python can be used in many avenues, it is easy to learn, and therefore it is no surprise that its popularity has been rising. In this article, let us take a look at why you should start learning python, especially if you want to do statistical modelling.

1.  Flexibility

Python can be used for almost all types of programming – you name it, it can do it. Be it statistical modelling in python, scientific of mathematical computing, finance, trading, game development or even penetration testing, python is suitable for all those activities. In fact, most of the python programmers say that almost all problems in programming can be solved using this multi-functional programming language.

2.    Data Science

Data science is the most trending aspect of computer programming today, and many companies have already started implementing analytics systems regardless of the field they operate in. Python and statistics have almost become synonymous now, and are usually mentioned in the same sentences as each other. Python is currently the most popular application in data engineering, and this has been one of the main reasons why it has become extremely popular today. Tools like NumPy, SciPy, Pandas and the many others available really do make life easier for a data scientist. Prototyping is remarkably easy using Python, and it would be the best choice for you if you want to build a career as a data scientist.

3.    Salary

Make no mistake, this is perhaps the most important and attractive part of why Python has become so popular. Some of the highest salaries in the industry, especially in the US, go to capable Python developers. Python is the second best-paying programming language to know, and it is only beaten by a small margin by Ruby – which is an extremely niche language to know. Considering its flexibility and ease to learn, Python is definitely the better one to start with among the two.

4.    Demand

As iterated earlier, the demand for capable Python developers is growing by the day. As companies become increasingly data-oriented, data analysts and scientists are finding increasingly lucrative job opportunities. There has been a steady growth in the demand for Python programmers ever since 2012, and it is within reach of most interested people. Start on your journey to learn statistics using Python if you want to tap into this!

5.    Time

Anyone who has learned Python would testify to the fact that it is an extremely efficient and quick language to use. Making any sort of application using Python would take a lot less time than using other languages, and the coding process is also considerably quicker than most. Also, learning Python from scratch is also extremely easy, since it does not have a rigid syntax like the other programming languages.

6.    Beginner Friendly

By now, you would have understood that Python is extremely beginner-friendly to learn. The code reads almost like English, and there are very few aspects regarding the syntax that you would have to learn to use it. Beginners will be able to focus on solving the process at hand, instead of having to spend a lot of time debugging the code for small syntax mistakes.

If you really want to start learning Python for data science, check out the courses offered by Acadgild!

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