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Data Analysis, Data Science & Visualization: Python & Pandas

Learn complete Data Analysis, Data Visualization & Data Science using Python and Pandas


Description

Why Data Analysis?

As organizations seek to create insights and push their businesses forward with the assistance of data, the field of data analytics is expanding at a fast pace. Learn what data analytics is, why it is important, the many kinds of data analytics, and the numerous data analytics applications in this Data Analytics Complete Course. You will also learn how to use data analytics.


Why Enroll in our course?

  1. 9Hours Intense content

  2. Full of practices and Hands on Projects

  3. FREE Textbook

  4. Community of Students and Experts

  5. Udemy Certificate

  6. 30 Days Money Back Grantee

What will we do in the course?

We'll go through hundreds of various methods, characteristics, features, and functions that are hidden away inside this incredible library during this session. We'll delve into a slew of various datasets, both short and lengthy, broken and immaculate, in order to show the amazing flexibility and effectiveness of this tool.


Data Analysis with Pandas and Python comes includes a slew of sample datasets that you may experiment with. Explore Pandas from the beginning and follow along with my tutorials to discover how simple it is to get started with pandas!


The Data Analysis with pandas and Python course is an excellent introduction to one of the most powerful data toolkits available today, whether you're a novice data analyst or have spent years (*cough* far too long *cough*) in Microsoft Excel.


Topics:

  • Introduction to Python course


  • Intermediate Python- Functions, Modules, Classes and Exceptions


  • Introduction Data Analysis in Python


  • Applied Data Analysis in Python - Machine learning and Data science


In data analysis using python python's ability to create and manage data structures quickly, for example, is one of the most common applications of the language in data analysis — Pandas, for example, provides a plethora of tools for manipulating, analyzing, and even representing complex datasets — and this is one of the most common applications of Python in data analysis.


We had a team people editing and marketing the course, the editing was done by Mohammad Chowdhury and the marketing was done by Mohammad Fahmid Chowdhury.


The course was created by professors with years of Python experience. The course content was created by Matt Williams, he is a professor with years of Python and Data Science experience, under the CC Attribution license.


Attributions:

Editing: Mohammad Chowdhury

Music: from Bensound

Thumbnail: by Alex Knight on Unsplash

Content creator: Matt Williams from University of Bristol

Created under CC attribution license

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