COVID19 Data Analysis Using Python
In this project, you will learn how to preprocess and merge datasets to calculate needed measures and prepare them for an Analysis. In this project, we are going to work with the COVID19 dataset, published by John Hopkins University, which consists of the data related to the cumulative number of confirmed cases, per day, in each Country. Also, we have another dataset consist of various life factors, scored by the people living in each country around the globe.
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- Level Intermediate
- Duration 3 hours
- Course by Coursera Project Network
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In this project, you will learn how to preprocess and merge datasets to calculate needed measures and prepare them for an Analysis. In this project, we are going to work with the COVID19 dataset, published by John Hopkins University, which consists of the data related to the cumulative number of confirmed cases, per day, in each Country. Also, we have another dataset consist of various life factors, scored by the people living in each country around the globe. We are going to merge these two datasets to see if there is any relationship between the spread of the virus in a country and how happy people are, living in that country. Notes: This project works best for learners who are based in the North America region. We're currently working on providing the same experience in other regions.Modules
Practical Application Using Guided Projects
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2
Readings
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1
Plugin
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1
Lab
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Assignment
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Assignment
- Test your Project understanding
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Labs
- Covid19 Data Analysis Using Python
2
Readings
- Project-based Course Overview
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Dive into the world of data analysis with the "COVID19 Data Analysis Using Python" course, designed for IT and Computer Science enthusiasts. This engaging project-based course, offered by Coursera and led by expert instructors, guides you through the process of preprocessing and merging datasets to uncover meaningful insights. You will work with a comprehensive COVID19 dataset from John Hopkins University, detailing the daily cumulative confirmed cases worldwide. Additionally, you will explore another dataset that captures various life factors and happiness scores from people in different countries. By merging these datasets, you will analyze potential correlations between the spread of the virus and the happiness levels in various nations. This professional-level course spans 120 hours and is available through a Starter subscription. While tailored for learners in North America, efforts are underway to extend this experience to other regions. Perfect for data enthusiasts looking to enhance their Python skills and gain insights into pandemic trends, this course offers a valuable and practical learning experience.
Ahmad Varasteh