Python world


 Description

The python language is one of the most accessible programming languages available because it has simplified syntax and not complicated, which gives more emphasis on natural language. Due to its ease of learning and usage, python codes can be easily written and executed much faster than other programming languages. Python is great for validating ideas or products for established companies. Python has many built-in testing frameworks that cover debugging & the fastest workflows. There are a lot of tools and modules to make things easier such as Selenium and Splinter. It supports testing with cross-platform & cross-browser frameworks such as PyTest and Robot Framework. Testing is a tedious task and Python is the booster for it, so every tester should definitely go for it!


Python handles a lot of hassles of data. It supports parallel computing where you can use Python for Hadoop as well. In Python, you have a library called “Pydoop” and you can write a MapReduce program in Python and process data present in the HDFS cluster.


There are other libraries such as ‘Dask‘ and ‘Pyspark‘ for big data processing. Therefore, Python is widely used for Big Data where you can easily process it!


Many people only know that Python is a programming language, but Python can also be used as the Scripting language. In scripting:


The code is written in the form of scripts and get executed


Machine reads and interprets the code


Error checking is done during Runtime


Once the code is checked, it can be used several times. So by automation, you can automate certain tasks in a program.


Python is the leading language of many data scientists. For years, academic scholars and private researchers were using the MATLAB language for scientific research but it all started to change with the release of Python numerical engines such as ‘Numpy’ and ‘Pandas’.


Python also deals with the tabular, matrix as well as statistical data and it even visualizes it with popular libraries such as ‘Matplotlib’ and ‘Seaborn‘.




Who this course is for:

Beginners Python developers who are curious about data science

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