R Programming
Keep adding new skills with 10,000+ programs for $239 (usually $399). Save now.
R Programming
This course is part of multiple programs.
751,159 already enrolled
Included with
Ask Coursera
22,373 reviews
Recommended experience
22,373 reviews
Recommended experience
What you'll learn
Understand critical programming language concepts
Configure statistical programming software
Make use of R loop functions and debugging tools
Collect detailed information using R profiler
Skills you'll gain
Tools you'll learn
Details to know
See how employees at top companies are mastering in-demand skills
Build your subject-matter expertise
- Learn new concepts from industry experts
- Gain a foundational understanding of a subject or tool
- Develop job-relevant skills with hands-on projects
- Earn a shareable career certificate
There are 4 modules in this 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.
This week covers the basics to get you started up with R. The Background Materials lesson contains information about course mechanics and some videos on installing R. The Week 1 videos cover the history of R and S, go over the basic data types in R, and describe the functions for reading and writing data. I recommend that you watch the videos in the listed order, but watching the videos out of order isn't going to ruin the story.
What's included
28 videos9 readings1 assignment7 programming assignments
28 videos•Total 129 minutes
- Installing R on a Mac•2 minutes
- Installing R on Windows•3 minutes
- Installing R Studio (Mac)•2 minutes
- Writing Code / Setting Your Working Directory (Windows)•7 minutes
- Writing Code / Setting Your Working Directory (Mac)•8 minutes
- Introduction•1 minute
- Overview and History of R•16 minutes
- Getting Help•14 minutes
- R Console Input and Evaluation•5 minutes
- Data Types - R Objects and Attributes•5 minutes
- Data Types - Vectors and Lists•6 minutes
- Data Types - Matrices•3 minutes
- Data Types - Factors•5 minutes
- Data Types - Missing Values•2 minutes
- Data Types - Data Frames•3 minutes
- Data Types - Names Attribute•2 minutes
- Data Types - Summary•1 minute
- Reading Tabular Data•6 minutes
- Reading Large Tables•7 minutes
- Textual Data Formats•5 minutes
- Connections: Interfaces to the Outside World•5 minutes
- Subsetting - Basics•4 minutes
- Subsetting - Lists•5 minutes
- Subsetting - Matrices•3 minutes
- Subsetting - Partial Matching•2 minutes
- Subsetting - Removing Missing Values•4 minutes
- Vectorized Operations•4 minutes
- Introduction to swirl•1 minute
9 readings•Total 90 minutes
- Welcome to R Programming•10 minutes
- About the Instructor•10 minutes
- Pre-Course Survey•10 minutes
- Syllabus•10 minutes
- Course Textbook•10 minutes
- Course Supplement: The Art of Data Science•10 minutes
- Data Science Podcast: Not So Standard Deviations•10 minutes
- Getting Started and R Nuts and Bolts•10 minutes
- Practical R Exercises in swirl Part 1•10 minutes
1 assignment•Total 40 minutes
- Week 1 Quiz•40 minutes
7 programming assignments•Total 1,260 minutes
- swirl Lesson 1: Basic Building Blocks•180 minutes
- swirl Lesson 2: Workspace and Files•180 minutes
- swirl Lesson 3: Sequences of Numbers•180 minutes
- swirl Lesson 4: Vectors•180 minutes
- swirl Lesson 5: Missing Values•180 minutes
- swirl Lesson 6: Subsetting Vectors•180 minutes
- swirl Lesson 7: Matrices and Data Frames•180 minutes
Welcome to Week 2 of R Programming. This week, we take the gloves off, and the lectures cover key topics like control structures and functions. We also introduce the first programming assignment for the course, which is due at the end of the week.
What's included
13 videos3 readings2 assignments3 programming assignments
13 videos•Total 91 minutes
- Control Structures - Introduction•1 minute
- Control Structures - If-else•2 minutes
- Control Structures - For loops•4 minutes
- Control Structures - While loops•3 minutes
- Control Structures - Repeat, Next, Break•5 minutes
- Your First R Function•10 minutes
- Functions (part 1)•9 minutes
- Functions (part 2)•7 minutes
- Scoping Rules - Symbol Binding•11 minutes
- Scoping Rules - R Scoping Rules•9 minutes
- Scoping Rules - Optimization Example (OPTIONAL)•9 minutes
- Coding Standards•9 minutes
- Dates and Times•10 minutes
3 readings•Total 30 minutes
- Week 2: Programming with R•10 minutes
- Practical R Exercises in swirl Part 2•10 minutes
- Programming Assignment 1 INSTRUCTIONS: Air Pollution•10 minutes
2 assignments•Total 60 minutes
- Week 2 Quiz•30 minutes
- Programming Assignment 1: Quiz•30 minutes
3 programming assignments•Total 540 minutes
- swirl Lesson 1: Logic•180 minutes
- swirl Lesson 2: Functions•180 minutes
- swirl Lesson 3: Dates and Times•180 minutes
We have now entered the third week of R Programming, which also marks the halfway point. The lectures this week cover loop functions and the debugging tools in R. These aspects of R make R useful for both interactive work and writing longer code, and so they are commonly used in practice.
What's included
8 videos2 readings1 assignment2 programming assignments1 peer review
8 videos•Total 61 minutes
- Loop Functions - lapply•9 minutes
- Loop Functions - apply•7 minutes
- Loop Functions - mapply•5 minutes
- Loop Functions - tapply•3 minutes
- Loop Functions - split•9 minutes
- Debugging Tools - Diagnosing the Problem•13 minutes
- Debugging Tools - Basic Tools•6 minutes
- Debugging Tools - Using the Tools•8 minutes
2 readings•Total 20 minutes
- Week 3: Loop Functions and Debugging•10 minutes
- Practical R Exercises in swirl Part 3•10 minutes
1 assignment•Total 30 minutes
- Week 3 Quiz•30 minutes
2 programming assignments•Total 360 minutes
- swirl Lesson 1: lapply and sapply•180 minutes
- swirl Lesson 2: vapply and tapply•180 minutes
1 peer review•Total 60 minutes
- Programming Assignment 2: Lexical Scoping •60 minutes
This week covers how to simulate data in R, which serves as the basis for doing simulation studies. We also cover the profiler in R which lets you collect detailed information on how your R functions are running and to identify bottlenecks that can be addressed. The profiler is a key tool in helping you optimize your programs. Finally, we cover the str function, which I personally believe is the most useful function in R.
What's included
6 videos4 readings2 assignments3 programming assignments
6 videos•Total 42 minutes
- The str Function•6 minutes
- Simulation - Generating Random Numbers•8 minutes
- Simulation - Simulating a Linear Model•5 minutes
- Simulation - Random Sampling•3 minutes
- R Profiler (part 1)•11 minutes
- R Profiler (part 2)•10 minutes
4 readings•Total 40 minutes
- Week 4: Simulation & Profiling•10 minutes
- Practical R Exercises in swirl Part 4•10 minutes
- Programming Assignment 3 INSTRUCTIONS: Hospital Quality•10 minutes
- Post-Course Survey•10 minutes
2 assignments•Total 60 minutes
- Week 4 Quiz•30 minutes
- Programming Assignment 3: Quiz•30 minutes
3 programming assignments•Total 540 minutes
- swirl Lesson 1: Looking at Data•180 minutes
- swrl Lesson 2: Simulation•180 minutes
- swirl Lesson 3: Base Graphics•180 minutes
Earn a career certificate
Add this credential to your LinkedIn profile, resume, or CV. Share it on social media and in your performance review.
Instructors
Offered by
Explore more from Data Analysis
- Status: Free TrialJ
Johns Hopkins University
Course
- Status: PreviewM
Microsoft
Course
- Status: Free TrialL
Logical Operations
Course
Why people choose Coursera for their career
Learner reviews
- 5 stars
68.05%
- 4 stars
22.12%
- 3 stars
5.82%
- 2 stars
2.09%
- 1 star
1.89%
Showing 3 of 22373
Reviewed on Sep 6, 2017
Great course for people who work with data a lot. This course actually helps in looking at data in its basic forms, helps understand transformations better, and gives ideas about playing with it.
Reviewed on May 26, 2017
This was very engaging, however, the level of expectation and effort needed is much greater than course 1 - ToolBox.This is perhaps the best course on R Programming designed for a small duration.
Reviewed on Feb 20, 2017
I am pleasantly surprised with the quality of this course. For a beginner, the Swirl exercises are incredibly helpful and I was able to build confidence in working with R because of them. Thank you!
Frequently asked questions
To access the course materials, assignments and to earn a Certificate, you will need to purchase the Certificate experience when you enroll in a course. You can try a Free Trial instead, or apply for Financial Aid. The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.
More questions
Financial aid available,