Whether you’re an aspiring data scientist or you’re already a data scientist looking to expand your skill set, know that the knowledge of Python is an essential skill in the field of data science. Python has become the preferred language in data analysis over the last few years, and it’s mainly due to its ease of learning and the fact that it is hugely time saving during application, though those are not the only reasons. Listed below are five reasons Data Science with Python training is essential for every data scientist. But, before we get to the why of learning this programming language, let’s understand what Python is.

What is Python?

Python is a versatile programming language that supports functional programming, structured programming, and also object Oriented programming. The versatility of this language is what makes it a good choice for data scientists. Python enables developers to create codes in a modular style and the codes can be reused as well, since Python supports the use of modules and packages.

Python is a simple and easy to learn programming language. It requires the use of a unique syntax which supports readability. It’s also a low-cost programming language. Python’s interpreter and standard library are available free of cost in binary and source form.

Python for Data Scientists

According to the Indeed Data Science skills report of April 2019, Python is among the top skills employers look for in data scientists, along with machine learning and SQL and Hadoop.Having these top skills not only boosts your resume but also gives you the chances of earning a higher salary. According to LinkedIn, data scientists with an updated skillset make an average of $107,000 a year.

Here are the top five reasons why you should take data science with Python training.

Scalable

Python is more scalable than R, making it more and more popular across various industries. It is also faster than Matlab and Sata. YouTube is one platform that uses Python because of its flexibility in problem solving situations.

Compatible with Hadoop

Python is compatible with Hadoop, the most popular open-source big data platform. The PyDoop package offers access to HDFS API for Hadoop, allowing programmers to write Hadoop MapReduce programs and applications. HDFS API allows you to connect to HDFS installation, which makes it easy to read, write, and get information on global file system properties, directories, and files.

Easy to Learn

Python is easy to learn for non-programmers too, compared to other programming languages. Due to its readable code, large online community, and varied learning resources, Python is a good choice to start learning programming language.

Extensive data science libraries

Python has over 72,000 libraries in the Python Package Index, making it popular among aspiring candidates. These libraries are upgraded regularly. Most of the libraries in Python are available for data analysis. Here are some of them.

• NumPy: The library has a number of high-level mathematical functions that operate on multidimensional arrays and matrices.
• SciPy:  It works in association with NumPy arrays and has routines for numerical integration and upgradation.
• Matplotlib: This is a 2D plotting library which contains data visualizations in the form of histograms, bar charts, and scatterplots with minimal coding lines.

Online Python Community

Python has increased its reach in the world of data science and a large number of volunteers are developing Python libraries. Due to this, it’s possible to develop advanced tools and processes in Python.

Which Skills Will You Learn?

Python is simple to learn, making it an ideal learning language for beginners. Read on to know which other skills you will learn with the data science with Python course.

1. You will get an in-depth understanding of data science processes, like data wrangling, data exploration, data visualization, and hypotheses building & testing.
2. You will be enabled to perform high-level mathematical calculations using the NumPy package.
3. You will gain expertise in machine learning using the Scikit-Learn package.
4. You will Understand how to use supervised and unsupervised learning models, such as linear regression, logistic regression, clustering, K-NN, and pipeline.
5. You will gain the knowledge to extract useful data from the websites with the help of web scraping using Python.
6. You will gain the ability to perform scientific and technical computing with SciPy package and its sub packages, like Integrate, Optimize, IO and Wave.

Data Science Is an Ever Expanding Field

Expanding consumerism has caused a surge in the demand for data scientists. Knowing the coding and programming tools and when to utilize their strengths to get the most out of your analysis is essential for a data scientist. Python is a popular programming language in data science, and a working knowledge of this language will give you a stepping stone to start your career as a data scientist.