About this Course
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Flexible deadlines

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Intermediate Level

Approx. 16 hours to complete

Suggested: 10 hours/week...

English

Subtitles: English

Skills you will gain

Data ManipulationRegular Expression (REGEX)R ProgrammingRstudio

100% online

Start instantly and learn at your own schedule.

Flexible deadlines

Reset deadlines in accordance to your schedule.

Intermediate Level

Approx. 16 hours to complete

Suggested: 10 hours/week...

English

Subtitles: English

Syllabus - What you will learn from this course

Week
1
2 hours to complete

Basic R Language

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
6 hours to complete

Basic R Language: Lesson Choices

2 quizzes
1 practice exercise
Swirl Lessons3h
Week
2
1 hour to complete

Data Manipulation

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
6 hours to complete

Data Manipulation: Lesson Choices

2 quizzes
1 practice exercise
Swirl Lessons3h
Week
3
1 hour to complete

Text Processing, Regular Expression, & Physical Memory

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
6 hours to complete

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

2 quizzes
1 practice exercise
Swirl Lessons3h
Week
4
5 hours to complete

Large Datasets

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 Instructions4h
1 practice exercise
Reading and Summarizing Data20m
4.4
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Top reviews from The R Programming Environment

By MVDec 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 KVJun 18th 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.

Instructors

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Roger D. Peng, PhD

Associate Professor, Biostatistics
Bloomberg School of Public Health
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Brooke Anderson

Assistant Professor, Environmental & Radiological Health Sciences
Colorado 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

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

Frequently Asked Questions

  • 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.

  • 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.

More questions? Visit the Learner Help Center.