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.
Dieser Kurs ist Teil der Spezialisierung Spezialisierung Mastering Software Development in R
von
Spezialisierung Mastering Software Development in RJohns Hopkins UniversityÜber diesen Kurs
Kompetenzen, die Sie erwerben
- Logic Programming
- R Programming
- Object-Oriented Programming (OOP)
- Functional Programming
von
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.
Lehrplan - Was Sie in diesem Kurs lernen werden
Welcome to Advanced R Programming
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.
Functions
This module begins with control structures in R for controlling the logical flow of an R program. We then move on to functions, their role in R programming, and some guidelines for writing good functions.
Functions: Lesson Choices
Functional Programming
Functional programming is a key aspect of R and is one of R's differentiating factors as a data analysis language. Understanding the concepts of functional programming will help you to become a better data science software developer. In addition, we cover error and exception handling in R for writing robust code.
Functional Programming: Lesson Choices
Debugging and Profiling
Debugging tools are useful for analyzing your code when it exhibits unexpected behavior. We go through the various debugging tools in R and how they can be used to identify problems in code. Profiling tools allow you to see where your code spends its time and to optimize your code for maximum efficiency.
Object-Oriented Programming
Object oriented programming allows you to define custom data types or classes and a set of functions for handling that data type in a way that you define. R has a three different methods for implementing object oriented programming and we will cover them in this section.
Bewertungen
- 5 stars58,88 %
- 4 stars22,62 %
- 3 stars10,41 %
- 2 stars2,87 %
- 1 star5,20 %
Top-Bewertungen von R-PROGRAMMIERUNG FÜR FORTGESCHRITTENE
That was exactly what I was looking for - first steprs In functional programming with perfect explanations and nice tasks via R :)
Great course but would prefer more video lectures versus text based lectures. Otherwise, a great course to help build out the foundations of R programming.
The last assignment did take a while but worth it. Really appreciate for proving such a well-organized course.
Very useful, I considered myself quite an advanced R user, but this class raised the level, especially with the R as OOB part. Good investment if you are not a beginner.
Über den Spezialisierung Mastering Software Development in R
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.
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