R is a fundamental language for data scientists, and this specialization provides a thorough understanding of R programming and tidyverse. It covers essential skills such as importing, tidying, and joining data, as well as crafting clear visualizations using the ggplot2 library. The capstone project allows learners to apply their knowledge to import, clean, and analyze data using R programming.
Throughout the three-course journey, participants will review programming fundamentals in R, understand the importance of reproducible research, and learn to use RMarkdown to share documents. The modules delve into identifying and transforming tidy data, analyzing data between multiple related data tables, and applying regular expressions to detect patterns in strings. By the end of the specialization, learners will be well-equipped to embark on a data science journey using R, making it an essential prerequisite for CU Boulder’s Master of Science in Data Science.
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The three-course specialization covers fundamental R programming and tidyverse skills, including data import, tidying, visualization, and reproducible research using RMarkdown. The capstone project enables learners to apply R programming to import, clean, and analyze data.
Introduction to R Programming and Tidyverse: This module provides a comprehensive overview of R programming and tidyverse, focusing on writing functions, analyzing and visualizing data sets, and sharing documents using RMarkdown.
Data Analysis with Tidyverse: Learners will gain expertise in identifying and transforming tidy data, analyzing data between multiple related data tables, and applying regular expressions to detect patterns in strings.
R Programming and Tidyverse Capstone Project: In this final module, participants will apply R programming to import, clean, and analyze data, culminating in a capstone project that demonstrates their acquired skills in data science using R.
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