R Programming: Conditionals, Loops, Functions, and Packages

R Programming: Conditionals, Loops, Functions, and Packages

This course is part of R Programming for Data Science Specialization

Instructor: Bill Rosenthal

3 modules

Gain insight into a topic and learn the fundamentals.

6 hours to complete

Flexible schedule

Learn at your own pace

3 modules

Gain insight into a topic and learn the fundamentals.

6 hours to complete

Flexible schedule

Learn at your own pace

What you'll learn

Implement conditional program logic using if-else structures, nested conditional statements, `is` functions, and the `%in%` membership operator.
Control execution flow with for and while loops alongside functional vectorized loop alternatives like `apply()`, `lapply()`, and `sapply()`.
Structure reusable code by defining custom functions with dynamic scope, lazy evaluation rules, and flexible ellipsis `(...)` arguments.
Data files for this course are provided in the first course of this specialization, "R Programming: Setup and Data Processing".

Skills you'll gain

Tools you'll learn

Details to know

Shareable certificate

Add to your LinkedIn profile

Assessments

1 assignment

Taught in English

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Build your subject-matter expertise

This course is part of the R Programming for Data Science Specialization

When you enroll in this course, you'll also be enrolled in this Specialization.

Learn new concepts from industry experts
Gain a foundational understanding of a subject or tool
Develop job-relevant skills with hands-on projects
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There are 3 modules in this course

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.

Like any modern programming language, R enables you to control the logical flow of a program. The main constructs for doing so are conditional statements and loops, which you'll implement in this lesson so that you can apply decision making to code.

What's included

1 reading4 plugins

Most languages excel at giving programmers the tools they need to make coding easier. Reusing code not only allows you to develop at a quicker pace, but it also makes your source code more readable. Inefficient and ugly code is incredibly difficult to maintain, so you'll leverage R's built-in reusable objects to avoid this pitfall