About 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.
Who is this class for: Some programming experience (in any language) is recommended.
Created by: Johns Hopkins University
Taught by: Roger D. Peng, PhD, Associate Professor, Biostatistics
Bloomberg School of Public Health
Taught by: Jeff Leek, PhD, Associate Professor, Biostatistics
Bloomberg School of Public Health
Taught by: Brian Caffo, PhD, Professor, Biostatistics
Bloomberg School of Public Health
| Basic Info |
Course 2 of 10 in the
Data Science Specialization.
|
| Level | Intermediate |
| Language | English, Subtitles: French, Japanese, Chinese (Simplified) |
| How To Pass | Pass all graded assignments to complete the course. |
| User Ratings |
Syllabus
WEEK 1
Week 1: Background, Getting Started, and Nuts & Bolts
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.
28 videos, 9 readings
- Reading: Welcome to R Programming
- Reading: About the Instructor
- Reading: Pre-Course Survey
- Reading: Syllabus
- Reading: Course Textbook
- Reading: Course Supplement: The Art of Data Science
- Reading: Data Science Podcast: Not So Standard Deviations
- Video: Installing R on a Mac
- Video: Installing R on Windows
- Video: Installing R Studio (Mac)
- Video: Writing Code / Setting Your Working Directory (Windows)
- Video: Writing Code / Setting Your Working Directory (Mac)
- Reading: Getting Started and R Nuts and Bolts
- Video: Introduction
- Video: Overview and History of R
- Video: Getting Help
- Video: R Console Input and Evaluation
- Video: Data Types - R Objects and Attributes
- Video: Data Types - Vectors and Lists
- Video: Data Types - Matrices
- Video: Data Types - Factors
- Video: Data Types - Missing Values
- Video: Data Types - Data Frames
- Video: Data Types - Names Attribute
- Video: Data Types - Summary
- Video: Reading Tabular Data
- Video: Reading Large Tables
- Video: Textual Data Formats
- Video: Connections: Interfaces to the Outside World
- Video: Subsetting - Basics
- Video: Subsetting - Lists
- Video: Subsetting - Matrices
- Video: Subsetting - Partial Matching
- Video: Subsetting - Removing Missing Values
- Video: Vectorized Operations
- Video: Introduction to swirl
- Reading: Practical R Exercises in swirl Part 1
- Ungraded Programming: swirl Lesson 1: Basic Building Blocks
- Ungraded Programming: swirl Lesson 2: Workspace and Files
- Ungraded Programming: swirl Lesson 3: Sequences of Numbers
- Ungraded Programming: swirl Lesson 4: Vectors
- Ungraded Programming: swirl Lesson 5: Missing Values
- Ungraded Programming: swirl Lesson 6: Subsetting Vectors
- Ungraded Programming: swirl Lesson 7: Matrices and Data Frames
Graded: Week 1 Quiz
WEEK 2
Week 2: Programming with R
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.
13 videos, 3 readings
- Reading: Week 2: Programming with R
- Video: Control Structures - Introduction
- Video: Control Structures - If-else
- Video: Control Structures - For loops
- Video: Control Structures - While loops
- Video: Control Structures - Repeat, Next, Break
- Video: Your First R Function
- Video: Functions (part 1)
- Video: Functions (part 2)
- Video: Scoping Rules - Symbol Binding
- Video: Scoping Rules - R Scoping Rules
- Video: Scoping Rules - Optimization Example (OPTIONAL)
- Video: Coding Standards
- Video: Dates and Times
- Reading: Practical R Exercises in swirl Part 2
- Ungraded Programming: swirl Lesson 1: Logic
- Ungraded Programming: swirl Lesson 2: Functions
- Ungraded Programming: swirl Lesson 3: Dates and Times
- Reading: Programming Assignment 1 INSTRUCTIONS: Air Pollution
Graded: Week 2 Quiz
Graded: Programming Assignment 1: Quiz
WEEK 3
Week 3: Loop Functions and Debugging
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.
8 videos, 2 readings
- Reading: Week 3: Loop Functions and Debugging
- Video: Loop Functions - lapply
- Video: Loop Functions - apply
- Video: Loop Functions - mapply
- Video: Loop Functions - tapply
- Video: Loop Functions - split
- Video: Debugging Tools - Diagnosing the Problem
- Video: Debugging Tools - Basic Tools
- Video: Debugging Tools - Using the Tools
- Reading: Practical R Exercises in swirl Part 3
- Ungraded Programming: swirl Lesson 1: lapply and sapply
- Ungraded Programming: swirl Lesson 2: vapply and tapply
Graded: Week 3 Quiz
Graded: Programming Assignment 2: Lexical Scoping
WEEK 4
Week 4: Simulation & Profiling
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.
6 videos, 4 readings
- Reading: Week 4: Simulation & Profiling
- Video: The str Function
- Video: Simulation - Generating Random Numbers
- Video: Simulation - Simulating a Linear Model
- Video: Simulation - Random Sampling
- Video: R Profiler (part 1)
- Video: R Profiler (part 2)
- Reading: Practical R Exercises in swirl Part 4
- Ungraded Programming: swirl Lesson 1: Looking at Data
- Ungraded Programming: swrl Lesson 2: Simulation
- Ungraded Programming: swirl Lesson 3: Base Graphics
- Reading: Programming Assignment 3 INSTRUCTIONS: Hospital Quality
- Reading: Post-Course Survey
Graded: Week 4 Quiz
Graded: Programming Assignment 3: Quiz
FAQs
How It Works
Coursework
Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.
Help from Your Peers
Connect with thousands of other learners and debate ideas, discuss course material, and get help mastering concepts.
Certificates
Earn official recognition for your work, and share your success with friends, colleagues, and employers.
Creators
Johns Hopkins University
The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.
Pricing
| Audit | Purchase Course | |
|---|---|---|
| Access to course materials | Available | Available |
| Access to graded materials | Not available | Available |
| Receive a final grade | Not available | Available |
| Earn a shareable Course Certificate | Not available | Available |
Ratings and Reviews
Very Nice Course.
the assignments might be a little bit difficult for beginners to start with but that is what which will trigger a hacker in you and in turn will compel you find the answers and explore new and innovative ways of solving highly convoluted problems
G
Coursera provides universal access to the world’s best education, partnering with top universities and organizations to offer courses online.
© 2017 Coursera Inc. All rights reserved.
JM
Muy buen curso