Colleagues, in the “Introduction to R” training you will master the basics of data analysis in R, including vectors, lists, and data frames, and practice R with real data sets. You’ll get started with basic operations, like using the console as a calculator and understanding basic data types in R. Once you’ve had a chance to practice, you’ll move on to creating vectors and try out your new R skills on a data set based on betting in Las Vegas. Next, you’ll learn how to work with matrices in R, learning how to create them, and perform calculations with them. You’ll also examine how R uses factors to store categorical data. Finally, you’ll explore how to work with R data frames and lists. Master the R Basics for Data Analysis - use R for your own data analysis. These sought-after skills can help you progress in your career and set you up for further learning. This course is part of several tracks, including Data Analyst with R, Data Scientist with R, and R Programming, all of which can help you develop your knowledge. Training modules include: 1) Intro to R Basics - learn how to use the console as a calculator and how to assign variables. You will also get to know the basic data types in , 2) Matrices - you will be able to create matrices and understand how to do basic computations with them. You will analyze the box office numbers of the Star Wars movies and learn how to use matrices in R, 3) Data frame - create a data frame, select interesting parts of a data frame, and order a data frame according to certain variables, 3) Vectors - learn how to analyze your gambling results using vectors in R. After completing this chapter, you will be able to create vectors in R, name them, select elements from them, and compare different vectors, 4) Factors - data often falls into a limited number of categories. Factors are very important in data analysis, so start learning how to create, subset, and compare them now, and 5) Lists - lists can hold components of different types, just as your to-do lists can contain different categories of tasks. This chapter will teach you how to create, name, and subset these lists.
Enroll today (teams & executives are welcome): https://datacamp.pxf.io/rQ61Yy
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Explore our Data-Driven Organizations Audible and Kindle book series on Amazon:
1 - Data-Driven Decision-Making (Audible) (Kindle)
2 - Implementing Data Science Methodology: From Data Wrangling to Data Viz (Audible) (Kindle)
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