Data Analysis with Tidyverse
This course is part of Expressway to Data Science: R Programming and Tidyverse.
This course cannot be purchased separately - to access the complete learning experience, graded assignments, and earn certificates, you'll need to enroll in the full Expressway to Data Science: R Programming and Tidyverse Specialization program. You can audit this specific course for free to explore the content, which includes access to course materials and lectures. This allows you to learn at your own pace without any financial commitment.
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What you'll learn
Learn to identify and transform data into tidy format
Master data analysis across multiple related tables
Apply regular expressions for pattern matching in strings
Manipulate categorical variables using factors
Use Tidyverse packages for efficient data manipulation
Skills you'll gain
This course includes:
2.83 Hours PreRecorded video
8 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
Shareable certificate
Get a Completion Certificate
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There are 5 modules in this course
This comprehensive course focuses on data analysis using the Tidyverse ecosystem in R. Students learn to work with tidy data principles, manipulate data across multiple tables, apply regular expressions for string manipulation, and handle categorical variables using factors. The curriculum covers importing data, data transformation with dplyr, string operations with stringr, and categorical data analysis with forcats, providing hands-on experience through practical exercises and peer-reviewed assignments.
Projects, Tibbles and Importing Data
Module 1 · 1 Hours to complete
Tidying Data
Module 2 · 4 Hours to complete
Relational Data
Module 3 · 2 Hours to complete
String Manipulation and Regular Expressions
Module 4 · 4 Hours to complete
Categorical Variables and Factors
Module 5 · 3 Hours to complete
Fee Structure
Individual course purchase is not available - to enroll in this course with a certificate, you need to purchase the complete Professional Certificate Course. For enrollment and detailed fee structure, visit the following: Expressway to Data Science: R Programming and Tidyverse
Instructor
Faculty Director of Data Science Programs
Dr. Jane Wall is the Faculty Director of the Data Science Graduate Program at the University of Colorado Boulder, a position she has held since 2021. With a unique blend of business acumen and technical expertise, she brings a diverse background to her role. Dr. Wall began her academic journey with undergraduate degrees in Classical Languages and Political Science, followed by two master’s degrees in Mathematics and Applied Mathematics from the University of Georgia. Her professional experience includes significant roles at IBM, where she worked as a software engineer and manager, as well as leadership positions in various software development companies.Dr. Wall returned to academia to earn her Ph.D. in Computational and Applied Mathematics from Rice University, focusing on computational neuroscience. She has developed and taught numerous data science courses, including "Statistical Programming in R" and "Data Science Practicum." At CU Boulder, she oversees both residential and online modes of the Data Science program, which includes innovative courses like "Algebra and Differential Calculus for Data Science" and "Introduction to R Programming and Tidyverse." Dr. Wall's commitment to advancing data science education is evident through her efforts to create robust curricula that prepare students for successful careers in this rapidly evolving field.
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Frequently asked questions
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