Python+data analysis and visualization Hands-on Training | Operating Systems Online Course by Udemy

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Python basic and advanced fundaments and Numpy, pandas, matplotlib, seaborn with Hands on and practice excercises

An excellent training about Operating Systems

Python+data analysis and visualization Hands-on Training

The objective of this course is to be adept in Python programming and the extensively used libraries with python i.e Numpy, Pandas, Matplotlib, Seaborn for data analysis and manipulation and visualization purposes. The course content is primarily in Hindi. We discuss Python from scratch and take it to next level with almost all the concepts in python with relevant examples and practice exercises. After python we’ll discuss in length about Numpy, pandas, matplotlib and seaborn with practice datasets present in these libraries. we’ll load the dataset in pandas dataframe and will see the powerful data manipulation and analysis we can do with pandas along with programming efficiency of python. We discuss matplotlib which is grandfather library for data visualization to lay the foundation and take it to next level with Seaborn with advanced modern looking plots to find intrinsic insights of the data. What you will learn in the courseInstallation and introduction to Anaconda Distribution an PythonInteracting with Python and Basic fundamentals:-data types, variables, operators in PythonControl structures: -Conditional Statements, loops, list comprehensionsData Structures in PythonFunctions and exception handlingDecorators, Mappers, Generators, FiltersFile handling Regular Expressions Modules and Packages: Using and Creating Object-Oriented Programming (OOP) with PythonData analysis and Visualization libraries: Numpy Pandas Matplotlib Seaborn The important features that you get with the course are:-1. Hands on training with live recorded sessions to help understand each concept in detail 2. Best set of relevant examples to clarify concepts along with practice exercises.3. Discussions of the practice exercises in recordings

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