R Programming
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.
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- Level Professional
- Duration 57 hours
- Course by Johns Hopkins University
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Offered by
About
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.Modules
Background Material
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5
Videos
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7
Readings
5
Videos
- Installing R on a Mac
- Installing R on Windows
- Installing R Studio (Mac)
- Writing Code / Setting Your Working Directory (Windows)
- Writing Code / Setting Your Working Directory (Mac)
7
Readings
- Welcome to R Programming
- About the Instructor
- Pre-Course Survey
- Syllabus
- Course Textbook
- Course Supplement: The Art of Data Science
- Data Science Podcast: Not So Standard Deviations
Week 1: Getting Started and R Nuts and Bolts
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22
Videos
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1
Readings
22
Videos
- Introduction
- Overview and History of R
- Getting Help
- R Console Input and Evaluation
- Data Types - R Objects and Attributes
- Data Types - Vectors and Lists
- Data Types - Matrices
- Data Types - Factors
- Data Types - Missing Values
- Data Types - Data Frames
- Data Types - Names Attribute
- Data Types - Summary
- Reading Tabular Data
- Reading Large Tables
- Textual Data Formats
- Connections: Interfaces to the Outside World
- Subsetting - Basics
- Subsetting - Lists
- Subsetting - Matrices
- Subsetting - Partial Matching
- Subsetting - Removing Missing Values
- Vectorized Operations
1
Readings
- Getting Started and R Nuts and Bolts
Quiz
-
1
Assignment
1
Assignment
- Week 1 Quiz
Practical R Exercises in swirl
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1
Videos
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1
Readings
-
7
Programming
- swirl Lesson 1: Basic Building Blocks
- swirl Lesson 2: Workspace and Files
- swirl Lesson 3: Sequences of Numbers
- swirl Lesson 4: Vectors
- swirl Lesson 5: Missing Values
- swirl Lesson 6: Subsetting Vectors
- swirl Lesson 7: Matrices and Data Frames
1
Videos
- Introduction to swirl
1
Readings
- Practical R Exercises in swirl Part 1
Week 2
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13
Videos
-
1
Readings
13
Videos
- Control Structures - Introduction
- Control Structures - If-else
- Control Structures - For loops
- Control Structures - While loops
- Control Structures - Repeat, Next, Break
- Your First R Function
- Functions (part 1)
- Functions (part 2)
- Scoping Rules - Symbol Binding
- Scoping Rules - R Scoping Rules
- Scoping Rules - Optimization Example (OPTIONAL)
- Coding Standards
- Dates and Times
1
Readings
- Week 2: Programming with R
Practical R Exercises in swirl
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1
Readings
-
3
Programming
- swirl Lesson 1: Logic
- swirl Lesson 2: Functions
- swirl Lesson 3: Dates and Times
1
Readings
- Practical R Exercises in swirl Part 2
Quiz
-
1
Assignment
1
Assignment
- Week 2 Quiz
Programming Assignment
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1
Readings
-
1
Assignment
1
Assignment
- Programming Assignment 1: Quiz
1
Readings
- Programming Assignment 1 INSTRUCTIONS: Air Pollution
Week 3
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8
Videos
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1
Readings
8
Videos
- Loop Functions - lapply
- Loop Functions - apply
- Loop Functions - mapply
- Loop Functions - tapply
- Loop Functions - split
- Debugging Tools - Diagnosing the Problem
- Debugging Tools - Basic Tools
- Debugging Tools - Using the Tools
1
Readings
- Week 3: Loop Functions and Debugging
Practical R Exercises in swirl
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1
Readings
-
2
Programming
- swirl Lesson 1: lapply and sapply
- swirl Lesson 2: vapply and tapply
1
Readings
- Practical R Exercises in swirl Part 3
Quiz
-
1
Assignment
1
Assignment
- Week 3 Quiz
Programming Assignment
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1
PeerReview
1
Peer Review
- Programming Assignment 2: Lexical Scoping
Week 4
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6
Videos
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1
Readings
6
Videos
- The str Function
- Simulation - Generating Random Numbers
- Simulation - Simulating a Linear Model
- Simulation - Random Sampling
- R Profiler (part 1)
- R Profiler (part 2)
1
Readings
- Week 4: Simulation & Profiling
Quiz
-
1
Assignment
1
Assignment
- Week 4 Quiz
Practical R Exercises in swirl
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1
Readings
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3
Programming
- swirl Lesson 1: Looking at Data
- swrl Lesson 2: Simulation
- swirl Lesson 3: Base Graphics
1
Readings
- Practical R Exercises in swirl Part 4
Programming Assignment
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1
Readings
-
1
Assignment
1
Assignment
- Programming Assignment 3: Quiz
1
Readings
- Programming Assignment 3 INSTRUCTIONS: Hospital Quality
Post-Course Survey
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1
Readings
1
Readings
- Post-Course Survey
Auto Summary
Discover the R Programming course by Coursera, tailored for professionals in Data Science & AI. Master R for effective data analysis, from installation to advanced statistical computing. Engage with practical topics, including data reading, function writing, debugging, and more. Available through Starter, Professional, and Paid subscriptions, this comprehensive course spans 3420 minutes, perfect for those seeking to elevate their data analysis skills.
Roger D. Peng, PhD
Jeff Leek, PhD
Brian Caffo, PhD