### About The Course

In this course you will learn how to program in R and how to use R for effective data analysis. You will learn how to install and configure software necessary for a statistical programming environment and describe generic programming language concepts as they are implemented in a high-level statistical language. The course covers practical issues in statistical computing which includes programming in R, reading data into R, accessing R packages, writing R functions, debugging, profiling R code, and organizing and commenting R code. Topics in statistical data analysis will provide working examples.

### Frequently Asked Questions

How do the courses in the Data Science Specialization depend on each other?

We have created a handy course dependency chart to help you see how the nine courses in the specialization depend on each other.

Will I get a Statement of Accomplishment after completing this class?

Yes. Students who successfully complete the class will receive a Statement of Accomplishment signed by the instructor.

What resources will I need for this class?

A computer is needed on which the R software environment can be installed (recent Mac, Windows, or Linux computers are sufficient).

How does this course fit into the Data Science Specialization?

This is the second course in the sequence. We strongly recommend that you take The Data Scientist's Toolbox before taking R Programming.

We have created a handy course dependency chart to help you see how the nine courses in the specialization depend on each other.

Will I get a Statement of Accomplishment after completing this class?

Yes. Students who successfully complete the class will receive a Statement of Accomplishment signed by the instructor.

What resources will I need for this class?

A computer is needed on which the R software environment can be installed (recent Mac, Windows, or Linux computers are sufficient).

How does this course fit into the Data Science Specialization?

This is the second course in the sequence. We strongly recommend that you take The Data Scientist's Toolbox before taking R Programming.

### Recommended Background

Some familiarity with programming concepts will be useful as well basic knowledge of statistical reasoning; Data Scientist's Toolbox