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

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1,148 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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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.

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

1,489,241 Learners

37 Courses

Brooke Anderson

Assistant Professor, Environmental & Radiological Health Sciences

Colorado State University

71,574 Learners

5 Courses

Offered by

Johns Hopkins University

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Syllabus - What you will learn from this course

Content Rating93%(6,018 ratings)

Week

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 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

6 hours to complete

Basic R Language: Lesson Choices

6 hours to complete

Week

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

Week

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

Week

Week 4

5 hours to complete

Large Datasets

5 hours to complete

7 readings

Reviews

4.3

321 reviews

5 stars
59.49%
4 stars
25.08%
3 stars
7.49%
2 stars
3.22%
1 star
4.70%

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 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.

by KVJun 17, 2019

A very good course to read and get the valuable content of R language. This is for the students who want to learn and practice the basic and some intermediate concepts of data manipulation.

by SBJul 20, 2018

Excellent class. I had already done a lot of the swirls and would have liked that to be in my record somewhere, although it really wasn't hard--and was probably good--to repeat them.

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