R Programming: Data Analysis and Modeling

Coursera MOOC / Non-credit USD 49
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R Programming: Data Analysis and Modeling

About this course

To round out your R programming skills, you'll dive into its data science capabilities by loading and saving data and manipulating data frames using base R and the dplyr package. You'll also analyze data by exploring its underlying distribution and identifying missing values. Then, you'll visualize data by using base R and ggplot2 to plot that data in various ways. Lastly, you'll create statistical and machine learning models in R that can make predictions and other estimations about data. This is the third and final course in a multi-course Specialization. All of the courses in this Specialization require that you have R and R Studio installed on a Windows PC. The course setup instructions provided in the first course go into more detail about the hardware and software requirements.

What you'll learn

  • manipulating data frames using base R and dplyr
  • visualizing data with base R and ggplot2
  • analyzing data distributions and identifying missing values
  • creating statistical and machine learning models in R

Course objectives

  • to develop skills in data manipulation and analysis using R
  • to learn data visualization techniques
  • to build predictive models using statistical and machine learning methods

Skills you'll gain

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