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Course Description

Visualization is one of the most simple and effective ways to find patterns in data. These patterns include: What is the general range and shape of the data set? Are there any clusters of observations? Which variables correlate with each other? Are there any obvious outliers?

As your data set grows in terms of the number of data points and variables, however, it becomes increasingly difficult to visualize all this information at once. At most, you can plot data points on a three-dimensional axis and add further distinctions of size, color, shape, and so on. Yet this can easily become too busy and difficult to read. How, then, do we find patterns in really big data sets?

In this course, you will explore several powerful and commonly utilized techniques for distilling patterns from data. You will implement each of these techniques using the free and open-source statistical programming language R with real-world data sets. The focus will be on making these methods accessible for you in your own work.

You are required to have completed the following course or have equivalent experience before taking this course:

  • Understanding Data Analytics

Faculty Author

Linda Nozick

Benefits to the Learner

  • Use data to identify useful association rules
  • Identify the principal components in a data set
  • Use the principal components to draw insights from the data
  • Use factor analysis to draw insights from a data set

Target Audience

  • Current and aspiring data scientists
  • Analysts
  • Engineers
  • Researchers
  • Technical managers

Applies Towards the Following Certificates

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Enroll Now - Select a section to enroll in
Type
2 week
Dates
Jun 05, 2024 to Jun 18, 2024
Total Number of Hours
20.0
Course Fee(s)
Standard Price $1,199.00
Type
2 week
Dates
Aug 14, 2024 to Aug 27, 2024
Total Number of Hours
20.0
Course Fee(s)
Standard Price $1,199.00
Type
2 week
Dates
Oct 23, 2024 to Nov 05, 2024
Total Number of Hours
20.0
Course Fee(s)
Standard Price $1,199.00
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