We recommend the Data Manipulation tracks
Data Manipulation
Real-world data is messy. That’s why packages like dplyr and tidyr are so valuable. Using these packages, you can take the pain out of data manipulation by extracting, filtering, and transforming your data, clearing a path for quick and reliable data analysis. If you want to improve your data wrangling skills, this is the track for you. You’ll learn how to prepare real-world data for analysis and grow your expertise as you work with multiple tables. You’ll also gain hands-on experience of how to combine, merge, and create visualizations. You'll apply your new-found data manipulation skills using dplyr to analyze voting data from the United Nations. Start this track and discover how dplyr and tidyr can save you time manipulating data.
Text Mining
Discover text mining in R and learn how to extract exciting insights from tweets, product reviews, and books through sentiment analysis in R. You’ll discover a range of approaches to organizing and analyzing text data from books, articles, documents, and more. You’ll get a primer into regular expressions and look at ways to search for common patterns in text effectively. As you progress, you’ll cover a range of tidyverse packages that can help with text analysis in R, including stringr and tidytext. As well as covering string manipulation and the bag of words technique for text mining in R, you’ll also look at how sentiment analysis works. By the time you finish, you’ll have a firm understanding of text analysis in R and will have the confidence to carry out your own text mining and sentiment analysis.
Tidyverse Fundamentals
Experience the whole data science pipeline, from importing and tidying data to wrangling and visualizing data to modeling and communicating with data. Gain exposure to each component of this pipeline from a variety of different perspectives in this tidyverse R track. You’ll start by exploring the fundamentals of the tidyverse, a collection of data science tools within R. Here, you’ll learn how to use the tidyverse to analyze and visualize your own data. You’ll cover how to reshape data with tidyr, and how to complete linear regressions in a tidy framework. As you progress, you’ll use your skills and knowledge to perform analysis on real data sets, learning how to use tidyverse tools to visualize and communicate your findings. By the time you finish, you’ll have explored several tools in the tidyverse and have the confidence to work with data sets using these tools.
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