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.
Este curso forma parte de Programa Especializado - Mastering Software Development in R
The R Programming Environment
ofrecido por
Acerca de este Curso
4.4
728 calificaciones
Habilidades que obtendrás
Data ManipulationRegular Expression (REGEX)R ProgrammingRstudio
Programa - Qué aprenderás en este curso
Semana
1Basic R Language
In this module, you'll learn the basics of R, including syntax, some tidy data principles and processes, and how to read data into R.
1 video (Total 2 minutos), 27 readings, 1 quiz
27 lecturas
Course Textbook: Mastering Software Development in R1m
Syllabus10m
Swirl Assignments10m
Datasets10m
Lesson Introduction2m
Evaluation3m
Objects1m
Numbers1m
Creating Vectors1m
Mixing Objects1m
Explicit Coercion3m
Matrices3m
Lists2m
Factors4m
Missing Values3m
Data Frames3m
Names4m
Attributes1m
Summary1m
The Importance of Tidy Data5m
The “Tidyverse”4m
Reading Tabular Data with the readr Package10m
Reading Web-Based Data1m
Flat files online10m
Requesting data through a web API10m
Scraping web data2m
Parsing JSON, XML, or HTML data3m
1 ejercicio de práctica
Swirl Lessonss
Semana
2Data Manipulation
During this module, you'll learn to summarize, filter, merge, and otherwise manipulate data in R, including working through the challenges of dates and times.
11 readings, 1 quiz
11 lecturas
Basic Data Manipulation10m
Piping7m
Summarizing data10m
Selecting and filtering data10m
Adding, changing, or renaming columns7m
Spreading and gathering data10m
Merging datasets10m
Working with Dates, Times, Time Zones3m
Converting to a date or date-time class7m
Pulling out date and time elements5m
Working with time zones8m
1 ejercicio de práctica
Swirl Lessonss
Semana
3Text Processing, Regular Expression, & Physical Memory
During this module, you'll learn to use R tools and packages to deal with text and regular expressions. You'll also learn how to manage and get the most from your computer's physical memory when working in R.
9 readings, 1 quiz
9 lecturas
Text Processing and Regular Expressions1m
Text Manipulation Functions in R10m
Regular Expressions15m
RegEx Functions in R5m
The stringr Package10m
Summary1m
The Role of Physical Memory10m
Back of the Envelope Calculations8m
Internal Memory Management in R5m
1 ejercicio de práctica
Swirl Lessonss
Semana
4Large Datasets
In this final module, you'll learn how to overcome the challenges of working with large datasets both in memory and out as well as how to diagnose problems and find help.
7 readings, 1 quiz
7 lecturas
Working with Large Datasets2m
In-memory strategies10m
Out-of-memory strategies10m
Diagnosing Problems5m
How to Google Your Way Out of a Jam5m
Asking for Help5m
Quiz Instructionss
1 ejercicio de práctica
Reading and Summarizing Data20m
42%
comenzó una nueva carrera después de completar estos cursos
33%
consiguió un beneficio tangible en su carrera profesional gracias a este curso
11%
consiguió un aumento de sueldo o ascenso
Principales revisiones
por VS•May 28th 2017
Good Practice..........!!!...really helpful for building data science concept through R Programming.........Really salute for hardworking of instructor..................!!!
por AH•Aug 5th 2017
The R Programing Environment is very supportive environment, and I appriciate the guideline and the materials. futhermore, the course was good begining. Thanks
Instructores
Roger D. Peng, PhD
Associate Professor, BiostatisticsBloomberg School of Public Health
Brooke Anderson
Assistant Professor, Environmental & Radiological Health SciencesColorado State University
Acerca de 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.
Acerca del programa especializado Mastering Software Development in R
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 useful data science results and products. You will obtain rigorous training in the R language, including the skills for handling complex data, building R packages and developing custom data visualizations. You will learn modern software development practices to build tools that are highly reusable, modular, and suitable for use in a team-based environment or a community of developers.
Preguntas Frecuentes
¿Cuándo podré acceder a las lecciones y tareas?
Una vez que te inscribes para obtener un Certificado, tendrás acceso a todos los videos, cuestionarios y tareas de programación (si corresponde). Las tareas calificadas por compañeros solo pueden enviarse y revisarse una vez que haya comenzado tu sesión. Si eliges explorar el curso sin comprarlo, es posible que no puedas acceder a determinadas tareas.
¿Qué recibiré si me suscribo a este Programa especializado?
Cuando te inscribes en un curso, obtienes acceso a todos los cursos que forman parte del Programa especializado y te darán un Certificado cuando completes el trabajo. Se añadirá tu Certificado electrónico a la página Logros. Desde allí, puedes imprimir tu Certificado o añadirlo a tu perfil de LinkedIn. Si solo quieres leer y visualizar el contenido del curso, puedes auditar el curso sin costo.
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