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.
- 5 stars58.85%
- 4 stars22.54%
- 3 stars10.37%
- 2 stars2.86%
- 1 star5.36%
來自高级 R 语言程序设计的熱門評論
Excellent subject matter. 4 stars instead of 5 is only because there was no video. I love the videos in the other courses in this track, since I am an auditory learner.
More advanced, challenging course. Still, enjoyable and enlightening. Mentoring on this course is really helpful too!
The last problem is unnecessarily difficult with little related teaching and learning material provided. Otherwise, the course is certainly well worth taking.
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.