About this Course

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Learner Career Outcomes

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started a new career after completing these courses

35%

got a tangible career benefit from this course

11%

got a pay increase or promotion
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level

Familiarity with regression is recommended.

Approx. 58 hours to complete
English
Subtitles: Arabic, French, Chinese (Simplified), Portuguese (Brazilian), Vietnamese, English, Spanish, Japanese...

What you will 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 will gain

Data AnalysisDebuggingR ProgrammingRstudio

Learner Career Outcomes

36%

started a new career after completing these courses

35%

got a tangible career benefit from this course

11%

got a pay increase or promotion
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Flexible deadlines
Reset deadlines in accordance to your schedule.
Intermediate Level

Familiarity with regression is recommended.

Approx. 58 hours to complete
English
Subtitles: Arabic, French, Chinese (Simplified), Portuguese (Brazilian), Vietnamese, English, Spanish, Japanese...

Offered by

Johns Hopkins University logo

Johns Hopkins University

Syllabus - What you will learn from this course

Content RatingThumbs Up94%(88,306 ratings)Info
Week
1

Week 1

25 hours to complete

Week 1: Background, Getting Started, and Nuts & Bolts

25 hours to complete
28 videos (Total 129 min), 9 readings, 8 quizzes
28 videos
Installing R on Windows3m
Installing R Studio (Mac)1m
Writing Code / Setting Your Working Directory (Windows)7m
Writing Code / Setting Your Working Directory (Mac)7m
Introduction1m
Overview and History of R16m
Getting Help13m
R Console Input and Evaluation4m
Data Types - R Objects and Attributes4m
Data Types - Vectors and Lists6m
Data Types - Matrices3m
Data Types - Factors4m
Data Types - Missing Values2m
Data Types - Data Frames2m
Data Types - Names Attribute1m
Data Types - Summary43s
Reading Tabular Data5m
Reading Large Tables7m
Textual Data Formats4m
Connections: Interfaces to the Outside World4m
Subsetting - Basics4m
Subsetting - Lists4m
Subsetting - Matrices2m
Subsetting - Partial Matching1m
Subsetting - Removing Missing Values3m
Vectorized Operations3m
Introduction to swirl1m
9 readings
Welcome to R Programming10m
About the Instructor10m
Pre-Course Survey10m
Syllabus10m
Course Textbook10m
Course Supplement: The Art of Data Science10m
Data Science Podcast: Not So Standard Deviations10m
Getting Started and R Nuts and Bolts10m
Practical R Exercises in swirl Part 110m
1 practice exercise
Week 1 Quiz40m
Week
2

Week 2

12 hours to complete

Week 2: Programming with R

12 hours to complete
13 videos (Total 91 min), 3 readings, 5 quizzes
13 videos
Control Structures - If-else1m
Control Structures - For loops4m
Control Structures - While loops3m
Control Structures - Repeat, Next, Break4m
Your First R Function10m
Functions (part 1)9m
Functions (part 2)7m
Scoping Rules - Symbol Binding10m
Scoping Rules - R Scoping Rules8m
Scoping Rules - Optimization Example (OPTIONAL)9m
Coding Standards8m
Dates and Times10m
3 readings
Week 2: Programming with R10m
Practical R Exercises in swirl Part 210m
Programming Assignment 1 INSTRUCTIONS: Air Pollution10m
2 practice exercises
Week 2 Quiz20m
Programming Assignment 1: Quiz20m
Week
3

Week 3

10 hours to complete

Week 3: Loop Functions and Debugging

10 hours to complete
8 videos (Total 61 min), 2 readings, 4 quizzes
8 videos
Loop Functions - apply7m
Loop Functions - mapply4m
Loop Functions - tapply3m
Loop Functions - split9m
Debugging Tools - Diagnosing the Problem12m
Debugging Tools - Basic Tools6m
Debugging Tools - Using the Tools8m
2 readings
Week 3: Loop Functions and Debugging10m
Practical R Exercises in swirl Part 310m
1 practice exercise
Week 3 Quiz10m
Week
4

Week 4

11 hours to complete

Week 4: Simulation & Profiling

11 hours to complete
6 videos (Total 42 min), 4 readings, 5 quizzes
6 videos
Simulation - Generating Random Numbers7m
Simulation - Simulating a Linear Model4m
Simulation - Random Sampling2m
R Profiler (part 1)10m
R Profiler (part 2)10m
4 readings
Week 4: Simulation & Profiling10m
Practical R Exercises in swirl Part 410m
Programming Assignment 3 INSTRUCTIONS: Hospital Quality10m
Post-Course Survey10m
2 practice exercises
Week 4 Quiz20m
Programming Assignment 3: Quiz20m

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