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Course Description

The real world is extremely complex, and revealing the patterns that underlie these complexities can be challenging. However, unlocking the power of a data set can provide you with remarkable insights and help guide decision-making. This course will prepare you to use summarization and visualization techniques to reveal patterns in real-world data, using examples from a variety of disciplines, including business and medicine.

In this course, Professor Basu will guide you as you begin to understand key data collection principles and how to make conclusions from data. Choosing which analyses to use depends on your question, so you will use a framework to help you choose which methods to use with your data. Then, you will use R to perform exploratory data analyses, which will allow you to identify key patterns and trends in a ready-to-analyze data set. You will also learn the importance of quantifying the uncertainty associated with your results, and how to measure variability in your data. This course involves many hands-on coding exercises in R to help you gain confidence in your programming skills.

System requirements: This course contains a virtual programming environment that does not support the use of Safari, Edge, tablets, or mobile devices. Please use Chrome, Firefox, or Internet Explorer on a computer for this course.

“Exploring Data Sets With R” must be completed prior to starting this course.

Faculty Author

Sumanta Basu

Benefits to the Learner

  • Understand data collection concepts and why correlation is not the same as causation
  • Summarize a data set with the appropriate visualizations and statistics
  • Use summarization techniques to interpret data and develop conclusions
  • Determine the uncertainty of your conclusions about a data set

Target Audience

  • Current and aspiring data scientists and analysts
  • Business decision makers
  • Marketing analysts
  • Consultants
  • Executives
  • Anyone seeking to gain deeper exposure to data science

Applies Towards the Following Certificates

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Cornell College of Computer and Information Science
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