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 stars68.10%
- 4 stars22.15%
- 3 stars5.84%
- 2 stars2.06%
- 1 star1.82%
TOP REVIEWS FROM R PROGRAMMING
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.
Fantastic course for learning R in a dynamic way, with clear goals. A lot of information is given, so I'd say that studying in between lectures is a must, if one wants to learn things really well.
Very challenging, but good course. I've been programming in R for over a year, but there were still some things for me to pick up in this class. Assignments were a challenge, but satisfying to tackle.
A great introduction to slightly more complicated R programming. Basic concepts covered well and it builds nicely to the point where you feel like you can apply your knowledge to real world examples
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