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.
This course is part of the Mastering Software Development in R Specialization
The R Programming Environment
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About this Course
4.4
750 ratings
Skills you will gain
Data ManipulationRegular Expression (REGEX)R ProgrammingRstudio
Syllabus - What you will learn from this course
Week
1Basic 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 video (Total 2 min), 27 readings
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
Basic R Language: Lesson Choices
2 quizzes
1 practice exercise
Swirl Lessonss
Week
2Data 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 readings
11 readings
Basic Data Manipulation10m
Piping7m
Summarizing data10m
Selecting and filtering data10m
Adding, changing, or renaming columns7m
Spreading and gathering data10m
Merging datasets10m
Working with Dates, Times, Time Zones3m
Converting to a date or date-time class7m
Pulling out date and time elements5m
Working with time zones8m
Data Manipulation: Lesson Choices
2 quizzes
1 practice exercise
Swirl Lessonss
Week
3Text 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 readings
9 readings
Text Processing and Regular Expressions1m
Text Manipulation Functions in R10m
Regular Expressions15m
RegEx Functions in R5m
The stringr Package10m
Summary1m
The Role of Physical Memory10m
Back of the Envelope Calculations8m
Internal Memory Management in R5m
Text Processing, Regular Expression, & Physical Memory: Lesson Choices
Choice 1: Get credit while using swirl | Choice 2: Get credit by providing a code from swirl
2 quizzes
1 practice exercise
Swirl Lessonss
Week
4Large 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 readings, 1 quiz
7 readings
Working with Large Datasets2m
In-memory strategies10m
Out-of-memory strategies10m
Diagnosing Problems5m
How to Google Your Way Out of a Jam5m
Asking for Help5m
Quiz Instructionss
1 practice exercise
Reading and Summarizing Data20m
4.4
197 Reviews45%
started a new career after completing these courses
40%
got a tangible career benefit from this course
13%
got a pay increase or promotion
Top Reviews
By MV•Dec 26th 2018
Very Very Rigorous Course for a beginner on R language and because of its nature, after completing just one course, I feel like I have gained a lot of knowledge and also familiarity with R language.
By VS•May 28th 2017
Good Practice..........!!!...really helpful for building data science concept through R Programming.........Really salute for hardworking of instructor..................!!!
Instructors
Roger D. Peng, PhD
Associate Professor, BiostatisticsBloomberg School of Public Health
Brooke Anderson
Assistant Professor, Environmental & Radiological Health SciencesColorado State University
About 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.
About the Mastering Software Development in R Specialization
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 useful data science results and products. You will obtain rigorous training in the R language, including the skills for handling complex data, building R packages and developing custom data visualizations. You will 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.
Frequently Asked Questions
When will I have access to the lectures and assignments?
Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.
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.
What is the refund policy?
Is financial aid available?
More questions? Visit the Learner Help Center.
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