Why Python Language is the Best Choice for Data Scientists?

27-Mar-2021

What is Python?

Python is a programming language which comes under the category of high-level programming languages. High-level programming languages are a certain category of programming languages which have certain features and characteristics which set them apart from low-level programming languages.

In the times when low-level programming languages were in common use, the field of programming was still in a nascent stage and was evolving slowly and gradually. As a result, many modern features of programming languages which programmers take for granted nowadays had not even been conceived by language designers back then.

So while low-level programming languages such as machine language and assembly language are extremely fast and efficient, they lack a lot of features which make programming smoother and simpler. Those features are all present in Python, a high-level programming language.

Those features are considered essential in any high-level programming language of today and Python counts as one of those. Some of the features which make programming so simple and convenient to do in Python are listed below.

Python has the following powerful features - built-in data structures, dynamic typing, dynamic binding, and functions. One big reason why Python is so attractive to data scientists is that it has built-in data structures. As a result, data scientists do not have to write the code for the various kinds of data structures from scratch.

The presence of dynamic binding in Python means that data scientists are not bound by the limitations of static typing in their code. They can take advantage of the enormous flexibility and the great amount of convenience that dynamic typing in Python offers.

The presence of functions means that data scientists can make their code neatly organized, modular, and divide it into small and manageable sections or chunks which can be understood easily.

Functions offer the added advantage that the same piece of code can be used again and again as one function can call another function and run its code to accomplish some task.

What is the scope of data science with python?

Data science with Python has a huge scope in the various sectors and industries of the world. There are many ways in which data science with Python can help the operations and functioning of the various sectors and industries of the world.

Python makes it incredibly simple and convenient to carry out the tasks commonly involved in the field of data science.

With the help of Python, data scientists are able to write large programs very easily and very quickly. Through the medium of these large programs, they are able to carry out complex analyses of the vast amount of data and extract concealed patterns from the data.

They then communicate this new information which they thus discover to the management staff of the company in which they are employed.

The management staff then puts their heads together with the data scientists and tries to make sense of the underlying patterns in the data. This activity is very important and it shows the scope of data science with Python.

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Once they have deduced the emerging trends from these underlying patterns they become fully-equipped to make the right decisions about the changes they should make in their business, operations, and way of doing things.

Since the data scientists have supplied them with meaningful information, they are now able to make business decisions in a data-driven way.

In many cases, the analyses carried out by data scientists using Python directly enable the management staff to understand the behaviour and psychology of their potential customers.

Once they are able to do this they can make changes to their business strategy to better target the needs, interests, concerns, expectations, and preferences of their potential customers.

Before the advent of data science with Python, businesses and organizations in the corporate world did not have a trustworthy and reliable way of understanding and predicting the behaviour of their potential customers.

They used to have to rely on their estimates and feelings for understanding and predicting the behaviour of their potential customers.

There was no systematic and organized way in which they could create a marketing strategy for their products and services which was tailored to the needs, interests, concerns, expectations, and preferences of their potential customers.

But with the advent of data science with Python, all this has become possible. Now companies possess all the information they require to craft and tailor their marketing strategy to the exact needs, interests, concerns, expectations, and preferences of their potential customers.

Companies value this ability very highly and therefore seek out skilled and competent data scientists actively.

Thus there is a huge demand for data scientists who are skilled and competent in the use of Python and also there is a huge scope of data science with Python in all the sectors and industries of the corporate world.

Which certification is good for python data science?

The best certification for Python with data science is the Data Science with Python course. This course has been carefully designed by our training institute to provide the best in class education and knowledge about data science with Python to the learners.

No stone has been left unturned to produce the most honed and refined course curriculum for the edification of the learners in the matter of performing the work of data science with the Python programming language.

Having observed the emerging trend in the data science community of using Python for most of the day-to-day tasks carried out by data scientists, our training institute decided to design a course which would enable learners to use Python to carry out tasks related to data science effectively.

The result is the data science with python course which is a course of such high quality and such exacting standards that even the most advanced and elevated experts will not be able to find a fault, flaw, or mistake in it.

We feel certain that the learners who take this data science with Python course will gain all the required skills and knowledge to become full-fledged data scientists in the real world and will be able to handle any and all projects assigned to them with ease and competence.

The following are some salient features of this data science with Python course -

1. The instructors -

The instructors for this data science with Python course can truly be said to be world-class in both their quality and their reputation. Our training institute followed a most complex selection procedure for acquiring these world-class instructors.

First, we identified the most reputable, eminent, and noteworthy teachers of data science with Python around the world. Next, we called them for written tests and several rounds of interviews. All in all, we put them through a most rigorous screening process in which they were tested extensively.

Due to the nature of this screening process, we can vouch for their teaching skills, their subject matter expertise, and their decades of experience from working in the field of data science with Python as professionals.

2. The course curriculum -

The course curriculum of the data science with Python course has been designed with the utmost care and with the most painstaking attention. Our experts have made sure to include all the most relevant and pertinent content related to the field of data science and Python in the course curriculum.

The course curriculum for this course will ensure that the learners are brought into contact with the most up-to-date and advanced knowledge and information related to the field of data science and Python. After taking this course they will become aware of all the most recent developments and advances in the field of data science and Python.

3. The feedback -

Throughout the duration of this course, the learners are assigned several assignments, surprise quizzes, and capstone projects. The learners are expected to complete these items and submit them to the instructors.

In turn, the instructors grade these submitted items by running an experienced eye over them and then they provide valuable feedback on each one of them. This feedback contains their appreciation, remarks, comments, and corrections to any mistakes the learners may have made.

4. The capstone projects -

The data science with Python course contains several capstone projects which are drawn from various fields in the corporate world. These capstone projects are based on a diverse range of topics and present the learners with several new concepts and challenges.

These capstone projects serve as a convenient and monitored way for the learners to acquire valuable practical and hands-on experience before they start their careers as data scientists in the real world.

Why does data science use Python only?

1. Python has a very well-developed library ecosystem -

The community of programmers and software developers who have gathered around the Python programming language over the past few decades has done a wonderful job in building and growing the Python library ecosystem.

Now Python virtually has a library for every problem a data scientist can encounter in his day-to-day work. With so many libraries, data scientists who use Python have no need to reinvent the wheel and write new code every time they encounter a problem in the course of their work.

2. Python has a very low entry barrier -

Python is probably the easiest to learn programming language out of all the programming languages that exist. This is because of several very good reasons. One of the biggest reasons is that Python has an extremely simple and beginner-friendly syntax.

Python makes use of whitespace for formatting and indentation. This makes Python code very easy to read and easy to parse. Also, the syntax of Python greatly resembles the natural languages used by humans and this makes Python code very accessible. These are some of the reasons why Python is very easy to learn and has a low entry barrier.

3. Python has a lot of flexibility compared to other programming languages -

Python allows the programmer to write code in several different styles such as the imperative style, the functional style, the object-oriented style, and the procedural style.

4. Python is platform-independent -

Python is available on Linux, Windows, macOS, and a variety of other platforms and Python code runs exactly the same on all these platforms.

Also Check:

Data Science with Python for Beginners

Is Python Good for Data Science?

Boost Your Career with Data Science Professional Certification

Is Machine Learning with Python Hard to Learn?

How Can I Learn Data Science from Scratch?

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