Link to Content:

R Programming

Created/Published/Taught by:

Coursera

Johns Hopkins University

Roger D. Peng

Jeff Leek

Brian Caffo

Content Found Via:

Coursera

Free? Partially: Some Free Content, Some Paid

Cost: $0.00

Tags: data analysis / data management / debugging / functions / programming / R

Difficulty Rating:

This is course 2 of 10 in the Coursera Data Science Specialization.

From Coursera:

“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.

Syllabus

- Week 1: Background, Getting Started, and Nuts & Bolts
- Week 2: Programming in R
- Week 3: Loop Functions and Debugging
- Week 4: Simulating & Profiling”

Recommended Prerequisites: Some programming experience (in any language)

Go to Content: R Programming

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