À propos de ce cours

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Résultats de carrière des étudiants

46%

ont commencé une nouvelle carrière après avoir terminé ce cours

42%

ont bénéficié d'un avantage concret dans leur carrières grâce à ce cours

13%

a obtenu une augmentation de salaire ou une promotion
Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Niveau intermédiaire
Approx. 27 heures pour terminer
Anglais
Sous-titres : Anglais, Français, Russe

Compétences que vous acquerrez

Data ManipulationRegular Expression (REGEX)R ProgrammingRstudio

Résultats de carrière des étudiants

46%

ont commencé une nouvelle carrière après avoir terminé ce cours

42%

ont bénéficié d'un avantage concret dans leur carrières grâce à ce cours

13%

a obtenu une augmentation de salaire ou une promotion
Certificat partageable
Obtenez un Certificat lorsque vous terminez
100 % en ligne
Commencez dès maintenant et apprenez aux horaires qui vous conviennent.
Dates limites flexibles
Réinitialisez les dates limites selon votre disponibilité.
Niveau intermédiaire
Approx. 27 heures pour terminer
Anglais
Sous-titres : Anglais, Français, Russe

Offert par

Logo Université Johns-Hopkins

Université Johns-Hopkins

Programme du cours : ce que vous apprendrez dans ce cours

Évaluation du contenuThumbs Up93%(5,429 notes)Info
Semaine
1

Semaine 1

2 heures pour terminer

Basic R Language

2 heures pour terminer
1 vidéo (Total 2 min), 27 lectures
27 lectures
Course Textbook: Mastering Software Development in R1 min
Syllabus10 min
Swirl Assignments10 min
Datasets10 min
Lesson Introduction2 min
Evaluation3 min
Objects1 min
Numbers1 min
Creating Vectors1 min
Mixing Objects1 min
Explicit Coercion3 min
Matrices3 min
Lists2 min
Factors4 min
Missing Values3 min
Data Frames3 min
Names4 min
Attributes1 min
Summary1 min
The Importance of Tidy Data5 min
The “Tidyverse”4 min
Reading Tabular Data with the readr Package10 min
Reading Web-Based Data1 min
Flat files online10 min
Requesting data through a web API10 min
Scraping web data2 min
Parsing JSON, XML, or HTML data3 min
6 heures pour terminer

Basic R Language: Lesson Choices

6 heures pour terminer
1 exercice pour s'entraîner
Swirl Lessons3 h
Semaine
2

Semaine 2

1 heure pour terminer

Data Manipulation

1 heure pour terminer
11 lectures
11 lectures
Basic Data Manipulation10 min
Piping7 min
Summarizing data10 min
Selecting and filtering data10 min
Adding, changing, or renaming columns7 min
Spreading and gathering data10 min
Merging datasets10 min
Working with Dates, Times, Time Zones3 min
Converting to a date or date-time class7 min
Pulling out date and time elements5 min
Working with time zones8 min
6 heures pour terminer

Data Manipulation: Lesson Choices

6 heures pour terminer
1 exercice pour s'entraîner
Swirl Lessons3 h
Semaine
3

Semaine 3

1 heure pour terminer

Text Processing, Regular Expression, & Physical Memory

1 heure pour terminer
9 lectures
9 lectures
Text Processing and Regular Expressions1 min
Text Manipulation Functions in R10 min
Regular Expressions15 min
RegEx Functions in R5 min
The stringr Package10 min
Summary1 min
The Role of Physical Memory10 min
Back of the Envelope Calculations8 min
Internal Memory Management in R5 min
6 heures pour terminer

Text Processing, Regular Expression, & Physical Memory: Lesson Choices

6 heures pour terminer
1 exercice pour s'entraîner
Swirl Lessons3 h
Semaine
4

Semaine 4

5 heures pour terminer

Large Datasets

5 heures pour terminer
7 lectures
7 lectures
Working with Large Datasets2 min
In-memory strategies10 min
Out-of-memory strategies10 min
Diagnosing Problems5 min
How to Google Your Way Out of a Jam5 min
Asking for Help5 min
Quiz Instructions4 h
1 exercice pour s'entraîner
Reading and Summarizing Data20 min

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À propos du Spécialisation Mastering Software Development in R

R is a programming language and a free software environment for statistical computing and graphics, widely used by data analysts, data scientists and statisticians. 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 and scaling useful data science results and products. This Specialization will give you rigorous training in the R language, including the skills for handling complex data, building R packages, and developing custom data visualizations. You’ll be introduced to indispensable R libraries for data manipulation, like tidyverse, and data visualization and graphics, like ggplot2. You’ll 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. This Specialization is designed to serve both data analysts, who may want to gain more familiarity with hands-on, fundamental software skills for their everyday work, as well as data mining experts and data scientists, who may want to use R to scale their developing and programming skills, and further their careers as data science experts....
Mastering Software Development in R

Foire Aux Questions

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