Johns Hopkins University

R Programming

This course is part of multiple programs.

Taught in English

Some content may not be translated

Roger D. Peng, PhD
Jeff Leek, PhD
Brian Caffo, PhD

Instructors: Roger D. Peng, PhD

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Course

Gain insight into a topic and learn the fundamentals

4.5

(22,178 reviews)

|

94%

Intermediate level

Recommended experience

57 hours (approximately)
Flexible schedule
Learn at your own pace

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

Details to know

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Assessments

6 quizzes

Course

Gain insight into a topic and learn the fundamentals

4.5

(22,178 reviews)

|

94%

Intermediate level

Recommended experience

57 hours (approximately)
Flexible schedule
Learn at your own pace

See how employees at top companies are mastering in-demand skills

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There are 4 modules in this course

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 quiz7 programming assignments

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 quizzes3 programming assignments

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 quiz2 programming assignments1 peer review

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 quizzes3 programming assignments

Instructors

Instructor ratings
4.4 (1,930 ratings)
Roger D. Peng, PhD
Johns Hopkins University
37 Courses1,573,014 learners

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4.5

22,178 reviews

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MS
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Reviewed on Mar 4, 2021

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5

Reviewed on Feb 20, 2017

JM
5

Reviewed on Aug 11, 2019

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