This course covers advanced topics in R programming that are necessary for developing powerful, robust, and reusable data science tools.

Johns Hopkins University Online Course Highlights

4 weeks long
4 hours a week
Learn for FREE, Upgradable
Self-Paced
Taught by: Brooke Anderson, Roger D. Peng
View Course Syllabus

Online Course Details:

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 re-usability within a team. For more information related online courses you can visit John Hopkins University Courses.

SKILLS YOU WILL GAIN

Logic Programming
R Programming
Object-Oriented Programming (OOP)
Functional Programming

Advanced R Programming