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.
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About this Course
Familiarity with regression is recommended.
Could your company benefit from training employees on in-demand skills?
Try Coursera for BusinessWhat 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 Analysis
- Debugging
- R Programming
- Rstudio
Familiarity with regression is recommended.
Could your company benefit from training employees on in-demand skills?
Try Coursera for BusinessOffered by
Syllabus - What you will learn from this course
Week 1: Background, Getting Started, and Nuts & Bolts
Week 2: Programming with R
Week 3: Loop Functions and Debugging
Week 4: Simulation & Profiling
Reviews
- 5 stars68.12%
- 4 stars22.14%
- 3 stars5.83%
- 2 stars2.06%
- 1 star1.82%
TOP REVIEWS FROM R PROGRAMMING
Really interesting course. The interactive coding sessions with swirl are especially useful. Would be great, if you provided sample solutions for the programming assignments, in particular for week 4.
This was very engaging, however, the level of expectation and effort needed is much greater than course 1 - ToolBox.
This is perhaps the best course on R Programming designed for a small duration.
I am pleasantly surprised with the quality of this course. For a beginner, the Swirl exercises are incredibly helpful and I was able to build confidence in working with R because of them. Thank you!
I would have preferred the 'robot voice' concept from the toolbox course, since it could be updated to more recent R upgrades, but the assignments really made me think and that was my favorite part.
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