Informações sobre o curso: 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.
Para quem é direcionado este curso: This course is aimed at learners who have some experience programming computers but who are not familiar with the R environment.
Desenvolvido por: Johns Hopkins University
Ministrado por: Roger D. Peng, PhD, Associate Professor, Biostatistics
Bloomberg School of Public HealthMinistrado por: Brooke Anderson, Assistant Professor, Environmental & Radiological Health Sciences
Colorado State University
| Informações básicas | Curso 1 de 5 no Mastering Software Development in R Specialization |
| Nível | Intermediário |
| Idioma | English |
| Como ser aprovado | Seja aprovado em todas as tarefas para concluir o curso. |
| Classificação do usuário |
Programa
SEMANA 1
Basic 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 videos, 27 leituras
- 阅读: Course Textbook: Mastering Software Development in R
- 阅读: Syllabus
- 阅读: Swirl Assignments
- 阅读: Datasets
- 阅读: Lesson Introduction
- 阅读: Evaluation
- 阅读: Objects
- 阅读: Numbers
- 阅读: Creating Vectors
- 阅读: Mixing Objects
- 阅读: Explicit Coercion
- 阅读: Matrices
- 阅读: Lists
- 阅读: Factors
- 阅读: Missing Values
- 阅读: Data Frames
- 阅读: Names
- 阅读: Attributes
- 阅读: Summary
- 阅读: The Importance of Tidy Data
- 阅读: The “Tidyverse”
- 阅读: Reading Tabular Data with the readr Package
- 阅读: Reading Web-Based Data
- 阅读: Flat files online
- 阅读: Requesting data through a web API
- 阅读: Scraping web data
- 阅读: Parsing JSON, XML, or HTML data
Nota atribuída: Swirl Lessons
SEMANA 2
Data 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 leituras
- 阅读: Basic Data Manipulation
- 阅读: Piping
- 阅读: Summarizing data
- 阅读: Selecting and filtering data
- 阅读: Adding, changing, or renaming columns
- 阅读: Spreading and gathering data
- 阅读: Merging datasets
- 阅读: Working with Dates, Times, Time Zones
- 阅读: Converting to a date or date-time class
- 阅读: Pulling out date and time elements
- 阅读: Working with time zones
Nota atribuída: Swirl Lessons
SEMANA 3
Text 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 leituras
- 阅读: Text Processing and Regular Expressions
- 阅读: Text Manipulation Functions in R
- 阅读: Regular Expressions
- 阅读: RegEx Functions in R
- 阅读: The stringr Package
- 阅读: Summary
- 阅读: The Role of Physical Memory
- 阅读: Back of the Envelope Calculations
- 阅读: Internal Memory Management in R
Nota atribuída: Swirl Lessons
SEMANA 4
Large 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 leituras
- 阅读: Working with Large Datasets
- 阅读: In-memory strategies
- 阅读: Out-of-memory strategies
- 阅读: Diagnosing Problems
- 阅读: How to Google Your Way Out of a Jam
- 阅读: Asking for Help
- 阅读: Quiz Instructions
Nota atribuída: Reading and Summarizing Data
Perguntas frequentes
Como funciona
课程作业
每门课程都像是一本互动的教科书，具有预先录制的视频、测验和项目。
来自同学的帮助
与其他成千上万的学生相联系，对想法进行辩论，讨论课程材料，并寻求帮助来掌握概念。
证书
获得正式认证的作业，并与朋友、同事和雇主分享您的成功。
Desenvolvedores
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.
Custo
| Comprar curso | |
|---|---|
| Acesso aos materiais do curso | Disponível |
| Acesso a materiais valendo nota | Disponível |
| Receba uma nota final | Disponível |
| Obtenha um Certificado de Curso compartilhável | Disponível |
Classificações e avaliações
Very challenging!
Excelente curso para los que comenzamos o ya tenemos un poco de experiencia con R. Es necesario saber inglés, pero me parace que con un nivel intermedio no tendrás ningún problema.
Very detailed with clear instruction of basics to a bit of advanced on R. A fantastic crash course for any beginner
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good exercises to help you get familiar (or revise) R programming concepts