Python for Data Analysis
Enroll in this free online Python for Data Analysis course to advance your career in the in-demand field of data analysis and learn about numerous tools and working methods for the libraries.
4.5
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3.0 Hrs
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About this course
Learn the fundamentals of data analysis with Python in this online course, where you'll be supervised by a subject-matter expert as you use Python Jupyter Notebook and associated libraries to analyze various datasets. You will have practical experience working with different types of datasets including IPL, football, and Marvel Superheroes datasets while developing engaging visualizations to portray the examined data. Additionally, you will learn how to use Python to load several dataset formats in the Notebook. After passing the exam, you will be awarded a certificate of completion for the course. Are you looking for a professional Data Science course to upgrade yourself with the concepts of data analysis? You can simply choose the Data Science course provided by the Great Learning platform that will help in building your career.
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Course Outline
EDA on IPL Data
In this module, the tutor will brief you about the libraries used for analyzing the data. You will also learn to code in Python Jupyter Notebook for analyzing the IPL dataset. Later on, you will learn to implement exploratory data analysis on the dataset using Python libraries – Pandas, matplotlib, and Seaborn.
EDA on Football Data
This module will comprehend you with another dataset of football. Later on, you will learn how to read the dataset in Jupyter Notebook. Then you will be introduced to various ways of data transformation of data using Python. Next, the tutor will show you various visualizations that you can use to analyze the data.
EDA on Marvel Superheroes Data
This is the last module, and you will use another dataset for data analysis. Here, the analysis will be done for the Marvel Superheroes dataset. Next, you will be familiarized with various kinds of immersive visuals that will reflect the analyzed data.
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