This course covers advanced topics in R programming that are necessary for developing powerful, robust, and reusable data science tools. Topics covered include functional programming in R, robust error handling, object oriented programming, profiling and benchmarking, debugging, and proper design of functions. Upon completing this course you will be able to identify and abstract common data analysis tasks and to encapsulate them in user-facing functions. Because every data science environment encounters unique data challenges, there is always a need to develop custom software specific to your organization’s mission. You will also be able to define new data types in R and to develop a universe of functionality specific to those data types to enable cleaner execution of data science tasks and stronger reusability within a team.
ジョンズ・ホプキンズ大学（Johns Hopkins University）
The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.
- 5 stars58.96%
- 4 stars22.58%
- 3 stars10.39%
- 2 stars2.86%
- 1 star5.19%
this is a must for those who want to improve their programming skills in R. As an advanced course, this is a little bit harder, but don`t give up!
The final homework assignment is tough if you are a newcomer to R. It is sink or swim time. Worth it if you can get through it.
That was exactly what I was looking for - first steprs In functional programming with perfect explanations and nice tasks via R :)
Good course, nothing much to say, definitely teaches the use of R, not quite sure it is "advanced" but I guess...
Mastering Software Development in R専門講座について
R is a programming language and a free software environment for statistical computing and graphics, widely used by data analysts, data scientists and statisticians. This Specialization covers R software development for building data science tools. As the field of data science evolves, it has become clear that software development skills are essential for producing and scaling useful data science results and products.