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.
Advanced R Programming
Dieser Kurs ist Teil von Spezialisierung Mastering Software Development in R
Dozenten: Roger D. Peng, PhD
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- Kategorie: Logic Programming
- Kategorie: R Programming
- Kategorie: Object-Oriented Programming (OOP)
- Kategorie: Functional Programming
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In diesem Kurs gibt es 7 Module
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.
Das ist alles enthalten
1 Video3 Lektüren
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.
Das ist alles enthalten
17 Lektüren
Das ist alles enthalten
1 Aufgabe1 Programmieraufgabe
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.
Das ist alles enthalten
19 Lektüren
Das ist alles enthalten
1 Aufgabe1 Programmieraufgabe
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.
Das ist alles enthalten
15 Lektüren1 Aufgabe
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.
Das ist alles enthalten
11 Lektüren1 peer review
Dozenten
Empfohlen, wenn Sie sich für Data Analysis interessieren
Johns Hopkins University
Johns Hopkins University
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Geprüft am 11. Feb. 2020
Geprüft am 17. Juli 2018
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