Overview

In our data-driven world, organizations need the right tools to extract valuable insights from that data. The R programming language is one of the tools at the forefront of data science. Its robust set of packages and statistical functions makes it a powerful choice for analyzing data, manipulating data, performing statistical tests on data, and creating predictive models from data. Likewise, R is notable for its strong data visualization tools, enabling you to create high-quality graphs and plots that are incredibly customizable. This Specialization will teach you the fundamentals of programming in R to get you started. It will also teach you how to use R to perform common data science tasks and achieve data-driven results for the business. This Specialization is designed for students who want to learn the R programming language, particularly students who want to leverage R for data analysis and data science tasks in their organization. The Specialization is also designed for students with an interest in applying statistics to real-world problems.

Syllabus

Course 1: R Programming: Setup and Data Processing
Course 2: R Programming: Conditionals, Loops, Functions, and Packages
Course 3: R Programming: Data Analysis and Modeling

Courses

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5 hours 30 minutes
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In this course, you'll continue to develop your R programming skills by writing conditional statements and loops—two of the most important constructs in any programming language. You'll also structure code for reuse by defining and calling functions, applying loop functions, and managing R packages. This is the second 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.
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18 hours
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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.
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10 hours 25 minutes
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This course will be useful to anyone who wants to learn the R programming language, particularly to leverage it for data analysis and data science tasks. You will begin by setting up an R development environment and executing simple code. Then, you'll process atomic data types like characters, numbers, and logical. You'll also process data structures like vectors, factors, and data frames. This is the first 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 module of this course go into more detail about the hardware and software requirements.