1,932 ratings
29,911 already enrolled
Learn the steps, needed to be taken to prepare your data sources for an analysis
Learn how to look at your data to find a good measure to stablish your analysis based upon
Learn to visualize the result of your analysis
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.
Python Programming
Data Analysis
Pandas
Seaborn
Statistics
In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:
Importing COVID19 dataset and preparing it for the analysis by dropping columns and aggregating rows.
Deciding on and calculating a good measure for our analysis.
Merging two datasets and finding correlations among our data.
Visualizing our analysis results using Seaborn.
Your workspace is a cloud desktop right in your browser, no download required
In a split-screen video, your instructor guides you step-by-step
by DG
Oct 29, 2020Very Informative. You do not have to know a lot of Programming to follow along, just a bit of basic should be Enough. Concepts are very well explained and the course is just at the right pace.
by PD
Jul 10, 2020great project for a beginner and intermediate to work upon, keep making these type of guided project and try to make it a bit lengthy(should be more 1 hour) :)
by DD
Nov 27, 2020i guess it is a fun course ad very easily managed via rhyme notebook. i guess anyone with interest in data science can come here and catch some curiosity or understand what they need to learn.
by CC
Jul 27, 2020Hi , this is chaandhini...very intresting course ...learned lots about data analysis using python...the instructor taught very friendly and really he is awesome...
By purchasing a Guided Project, you'll get everything you need to complete the Guided Project including access to a cloud desktop workspace through your web browser that contains the files and software you need to get started, plus step-by-step video instruction from a subject matter expert.
Because your workspace contains a cloud desktop that is sized for a laptop or desktop computer, Guided Projects are not available on your mobile device.
Guided Project instructors are subject matter experts who have experience in the skill, tool or domain of their project and are passionate about sharing their knowledge to impact millions of learners around the world.
You can download and keep any of your created files from the Guided Project. To do so, you can use the “File Browser” feature while you are accessing your cloud desktop.
Guided Projects are not eligible for refunds. See our full refund policy.
Financial aid is not available for Guided Projects.
Auditing is not available for Guided Projects.
At the top of the page, you can press on the experience level for this Guided Project to view any knowledge prerequisites. For every level of Guided Project, your instructor will walk you through step-by-step.
Yes, everything you need to complete your Guided Project will be available in a cloud desktop that is available in your browser.
You'll learn by doing through completing tasks in a split-screen environment directly in your browser. On the left side of the screen, you'll complete the task in your workspace. On the right side of the screen, you'll watch an instructor walk you through the project, step-by-step.
More questions? Visit the Learner Help Center.
