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.
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 | Inglês |
| Como ser aprovado | Seja aprovado em todas as tarefas para concluir o curso. |
| Classificação do usuário |
- Reading: Course Textbook: Mastering Software Development in R
- Reading: Syllabus
- Reading: Swirl Assignments
- Reading: Datasets
- Reading: Lesson Introduction
- Reading: Evaluation
- Reading: Objects
- Reading: Numbers
- Reading: Creating Vectors
- Reading: Mixing Objects
- Reading: Explicit Coercion
- Reading: Matrices
- Reading: Lists
- Reading: Factors
- Reading: Missing Values
- Reading: Data Frames
- Reading: Names
- Reading: Attributes
- Reading: Summary
- Reading: The Importance of Tidy Data
- Reading: The “Tidyverse”
- Reading: Reading Tabular Data with the readr Package
- Reading: Reading Web-Based Data
- Reading: Flat files online
- Reading: Requesting data through a web API
- Reading: Scraping web data
- Reading: Parsing JSON, XML, or HTML data
- Reading: Basic Data Manipulation
- Reading: Piping
- Reading: Summarizing data
- Reading: Selecting and filtering data
- Reading: Adding, changing, or renaming columns
- Reading: Spreading and gathering data
- Reading: Merging datasets
- Reading: Working with Dates, Times, Time Zones
- Reading: Converting to a date or date-time class
- Reading: Pulling out date and time elements
- Reading: Working with time zones
- Reading: Text Processing and Regular Expressions
- Reading: Text Manipulation Functions in R
- Reading: Regular Expressions
- Reading: RegEx Functions in R
- Reading: The stringr Package
- Reading: Summary
- Reading: The Role of Physical Memory
- Reading: Back of the Envelope Calculations
- Reading: Internal Memory Management in R
- Reading: Working with Large Datasets
- Reading: In-memory strategies
- Reading: Out-of-memory strategies
- Reading: Diagnosing Problems
- Reading: How to Google Your Way Out of a Jam
- Reading: Asking for Help
- Reading: Quiz Instructions
Cada curso es como un libro de texto interactivo, con videos pregrabados, cuestionarios y proyectos.
Conéctate con miles de estudiantes y debate ideas y materiales del curso, y obtén ayuda para dominar los conceptos.
Obtén reconocimiento oficial por tu trabajo y comparte tu éxito con amigos, compañeros y empleadores.
| 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 |
Excellent tour of basic R programming with many examples and well thought out assignments . The final project uses a real life data set and it was fun to use dplyr piping to find the correct answers. The Swirl program, which is downloaded inside of R as a package and is used for grading, was a little cumbersome at first, but once you get the hang of it, then it's not bad. Hang in there and don't give up.
I keep learning new things with these courses. Very Valuable.
The Swirl interactive course materials are really helpful for hand-on practice in R-studio. Learned a lot of R fundamentals. Recommended.
EL
Excelent course!