This course is part of the Mastering Software Development in R Specialization

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stars
1,149 ratings

Roger D. Peng, PhD +1 more instructor

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Mastering Software Development in R SpecializationJohns Hopkins University

About this Course

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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.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

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Coursera Labs

Includes hands on learning projects.

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Course 1 of 5 in the

Mastering Software Development in R Specialization

Intermediate Level

Approx. 27 hours to complete

English

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Skills you will gain

Data Manipulation
Regular Expression (REGEX)
R Programming
Rstudio

Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Coursera Labs

Includes hands on learning projects.

Learn more about Coursera Labs

Course 1 of 5 in the

Mastering Software Development in R Specialization

Intermediate Level

Approx. 27 hours to complete

English

Could your company benefit from training employees on in-demand skills?

Try Coursera for Business

Instructors

Instructor rating

4.06/5 (81 Ratings)

Roger D. Peng, PhD

Associate Professor, Biostatistics

Bloomberg School of Public Health

1,499,563 Learners

37 Courses

Brooke Anderson

Assistant Professor, Environmental & Radiological Health Sciences

Colorado State University

71,916 Learners

5 Courses

Offered by

Johns Hopkins University

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Syllabus - What you will learn from this course

Content Rating93%(6,042 ratings)

Week1

Week 1

2 hours to complete

Basic R Language

2 hours to complete

1 video (Total 2 min), 27 readings

1 video

Welcome to the R Programming Environment1m

27 readings

Course Textbook: Mastering Software Development in R1mSyllabus10mSwirl Assignments10mDatasets10mLesson Introduction2mEvaluation3mObjects1mNumbers1mCreating Vectors1mMixing Objects1mExplicit Coercion3mMatrices3mLists2mFactors4mMissing Values3mData Frames3mNames4mAttributes1mSummary1mThe Importance of Tidy Data5mThe “Tidyverse”4mReading Tabular Data with the readr Package10mReading Web-Based Data1mFlat files online10mRequesting data through a web API10mScraping web data2mParsing JSON, XML, or HTML data3m

6 hours to complete

Basic R Language: Lesson Choices

6 hours to complete

Week2

Week 2

1 hour to complete

Data Manipulation

1 hour to complete

11 readings

6 hours to complete

Data Manipulation: Lesson Choices

6 hours to complete

Week3

Week 3

1 hour to complete

Text Processing, Regular Expression, & Physical Memory

1 hour to complete

9 readings

6 hours to complete

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

6 hours to complete

Week4

Week 4

5 hours to complete

Large Datasets

5 hours to complete

7 readings

Reviews

4.3

321 reviews

5 stars
59.44%
4 stars
25.15%
3 stars
7.48%
2 stars
3.22%
1 star
4.69%

TOP REVIEWS FROM THE R PROGRAMMING ENVIRONMENT

by AHAug 4, 2017

The R Programing Environment is very supportive environment, and I appriciate the guideline and the materials. futhermore, the course was good begining. Thanks

by CNOct 23, 2020

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.

by TWApr 25, 2021

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.

by TSSep 13, 2021

Great Introduction, may we worth clarifying that for Data Manipulation the script must be saved before entering submit() as you cannot make progress.

View all reviews

About the Mastering Software Development in R Specialization

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.

Frequently Asked Questions

When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

More questions? Visit the Learner Help Center.

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The R Programming Environment

About this Course

Skills you will gain