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Learner Reviews & Feedback for Scatter Plot for Data Scientists & Big Data Analysts-Visuals by Coursera Project Network

About the Course

This project gives you easy access to the invaluable learning techniques used by experts for visualization in statistics. We’ll learn about how to use wolfram language to draw curve in easiest way. We’ll also cover illustration and best practices shown by research to be most effective in helping you master plotting curves. Using these approaches, no matter what your skill levels in topics you would like to master, you can change your thinking and change your life. If you’re already an expert, this peep under the mental hood will give you ideas for turbocharging successful learning, including counter-intuitive test-taking tips and insights that will help you make the best use of your time on homework and problem sets. If you’re struggling, you’ll see a structured treasure trove of practical techniques that walk you through what you need to do to get on track. If you’ve ever wanted to become better at anything, this project will help serve as your guide. In this project we will take some illustrations and be able to Visualize the data by Scatter Plot using Wolfram Mathematica. By the end of this project learners will: Be able to plot basic examples (list of y values and x y pair)& several data items with legends (labeling each Plot and each data item) Be able to plot values including 'units' and using individual 'color' for each point Be able to plot the range where the data is non real are excluded & function ranges where it is selected automatically....

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1 - 2 of 2 Reviews for Scatter Plot for Data Scientists & Big Data Analysts-Visuals

By Arya S

Mar 28, 2021

The Instructor did a Phenomenal job explaining concepts that build the foundations for Data Visualization and Analytics. The concept of Scatter plots was thoroughly understood through this guided project.

By Wijesinghe I

Apr 2, 2021

It's a great opportunity to improve my knowledge. Thanks, Coursera community for your prompt consideration.