Introduction to R Programming and 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.
4.3
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What you'll learn
Write and understand R functions for data analysis
Create data visualizations using ggplot2
Analyze datasets using dplyr and Tidyverse packages
Produce professional reports with RMarkdown
Apply programming principles to solve data problems
Skills you'll gain
This course includes:
3.05 Hours PreRecorded video
7 quizzes
Access on Mobile, Tablet, Desktop
FullTime access
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There are 4 modules in this course
This comprehensive introduction to R programming is designed for beginners from non-STEM backgrounds. The course covers fundamental R programming concepts, data visualization using ggplot2, and data analysis with dplyr and other Tidyverse packages. Students learn to create functions, analyze datasets, and produce professional reports using RMarkdown. The course emphasizes practical, hands-on learning with real-world applications in data science.
Introduction to R, RStudio and RMarkdown
Module 1 · 6 Hours to complete
Functions
Module 2 · 6 Hours to complete
Data Visualization using ggplot2
Module 3 · 3 Hours to complete
Data Analysis with dplyr
Module 4 · 6 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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4.3 course rating
40 ratings
Frequently asked questions
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