What Is Team Management: Strategies, Duties, Job, Career Outlook
January 21, 2025
Article
Develop Insights from Data With Tidy Tools. Import, wrangle, visualize, and model data with the Tidyverse R packages
Instructors: Stephanie Hicks, PhD
3,295 already enrolled
Included with
(96 reviews)
Recommended experience
Beginner level
Familiarity with the R programming language.
(96 reviews)
Recommended experience
Beginner level
Familiarity with the R programming language.
Organize a data science project
Import data from common spreadsheet, database, and web-based formats
Wrangle and manipulate messy data and build tidy datasets
Build presentation quality data graphics
Build predictive machine learning models
Add to your LinkedIn profile
Add this credential to your LinkedIn profile, resume, or CV
Share it on social media and in your performance review
This Specialization is intended for data scientists with some familiarity with the R programming language who are seeking to do data science using the Tidyverse family of packages. Through 5 courses, you will cover importing, wrangling, visualizing, and modeling data using the powerful Tidyverse framework. The Tidyverse packages provide a simple but powerful approach to data science which scales from the most basic analyses to massive data deployments. This course covers the entire life cycle of a data science project and presents specific tidy tools for each stage.
Applied Learning Project
Learners will engage in a project at the end of each course. Through each project, learners will build an organize a data science project from scratch, import and manipulate data from a variety of data formats, wrangle non-tidy data into tidy data, visualize data with ggplot2, and build machine learning prediction models.
Distinguish between tidy and non-tidy data
Describe how non-tidy data can be transformed into tidy data
Describe the Tidyverse ecosystem of packages
Organize and initialize a data science project
Describe different data formats
Apply Tidyverse functions to import data into R from external formats
Obtain data from a web API
Apply Tidyverse functions to transform non-tidy data to tidy data
Conduct basic exploratory data analysis
Conduct analyses of text data
Distinguish between various types of plots and their uses
Use the ggplot2 R package to develop data visualizations
Build effective data summary tables
Build data animations for visual storytelling
Describe different types of data analytic questions
Conduct hypothesis tests of your data
Apply linear modeling techniques to answer multivariable questions
Apply machine learning workflows to detect complex patterns in your data
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.
Unlimited access to 10,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription
Earn a degree from world-class universities - 100% online
Upskill your employees to excel in the digital economy
This Specialization will take approximately 12-15 weeks.
Some familiarity with the R programming language is required.
The courses are cumulative, so it is recommended that students take the courses in order.
No.
This course is completely online, so there’s no need to show up to a classroom in person. You can access your lectures, readings and assignments anytime and anywhere via the web or your mobile device.
If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.
Yes! To get started, click the course card that interests you and enroll. You can enroll and complete the course to earn a shareable certificate, or you can audit it to view the course materials for free. When you subscribe to a course that is part of a Specialization, you’re automatically subscribed to the full Specialization. Visit your learner dashboard to track your progress.
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.
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. If you only want to read and view the course content, you can audit the course for free. If you cannot afford the fee, you can apply for financial aid.
These cookies are necessary for the website to function and cannot be switched off in our systems. They are usually only set in response to actions made by you which amount to a request for services, such as setting your privacy preferences, logging in or filling in forms. You can set your browser to block or alert you about these cookies, but some parts of the site will not then work.
These cookies may be set through our site by our advertising partners. They may be used by those companies to build a profile of your interests and show you relevant adverts on other sites. They are based on uniquely identifying your browser and internet device. If you do not allow these cookies, you will experience less targeted advertising.
These cookies allow us to count visits and traffic sources so we can measure and improve the performance of our site. They help us to know which pages are the most and least popular and see how visitors move around the site. If you do not allow these cookies we will not know when you have visited our site, and will not be able to monitor its performance.
These cookies enable the website to provide enhanced functionality and personalization. They may be set by us or by third party providers whose services we have added to our pages. If you do not allow these cookies then some or all of these services may not function properly.