This course provides a rigorous introduction to the R programming language, with a particular focus on using R for software development in a data science setting. Whether you are part of a data science team or working individually within a community of developers, this course will give you the knowledge of R needed to make useful contributions in those settings. As the first course in the Specialization, the course provides the essential foundation of R needed for the following courses. We cover basic R concepts and language fundamentals, key concepts like tidy data and related "tidyverse" tools, processing and manipulation of complex and large datasets, handling textual data, and basic data science tasks. Upon completing this course, learners will have fluency at the R console and will be able to create tidy datasets from a wide range of possible data sources.
Dieser Kurs ist Teil der Spezialisierung Spezialisierung Mastering Software Development in R
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Spezialisierung Mastering Software Development in RJohns Hopkins UniversityÜber diesen Kurs
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- Data Manipulation
- Regular Expression (REGEX)
- R Programming
- Rstudio
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Lehrplan - Was Sie in diesem Kurs lernen werden
Basic R Language
Basic R Language: Lesson Choices
Data Manipulation
Data Manipulation: Lesson Choices
Text Processing, Regular Expression, & Physical Memory
Text Processing, Regular Expression, & Physical Memory: Lesson Choices
Large Datasets
Bewertungen
- 5 stars59,44 %
- 4 stars25,15 %
- 3 stars7,48 %
- 2 stars3,22 %
- 1 star4,69 %
Top-Bewertungen von THE R PROGRAMMING ENVIRONMENT
I liked the swirl() package a lot, made me jump into writing codes into RStudio straight away. My only wish was to have some videos that would push me further
A thorough course that covers a lot of efficient data manipulation styles within the R environment. I learned a lot of neat tricks that help with quick analysis of large data frames.
The whole course was easy to follow except for the last questions of the last exam where the merged data set results into a null data frame after filtering.
The R Programing Environment is very supportive environment, and I appriciate the guideline and the materials. futhermore, the course was good begining. Thanks
Über den Spezialisierung Mastering Software Development in R
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