R for Data Science: RStudio 1.1.4 Intermediate

  • 7 Courses | 5h 21m 3s
  • 10 Books | 44h 23m
  • 1 Audiobook | 8h 9m 58s
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Data science is a multi-disciplinary field used to analyze large amounts of data to detect relationships and uncover meaning. Discover how the R programming language can be used with data.

GETTING STARTED

R Data Structures

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COURSES INCLUDED

R Data Structures
R is a programming language that is an essential skill for statistical computing and graphics. It is the tool of choice for data science professionals in every industry and field—not only to create reproducible high-quality analyses, but to take advantage of R's great graphic and charting capabilities. In this 11-video Skillsoft Aspire course, you will explore the fundamental data structures used in R, including working with vectors, lists, matrices, factors, and data frames. The key concepts in this course include: creating vectors in R and manipulating and performing operations on vectors in R; how to sort vectors in R; and how to use lists in R and explore example code line by line executing each line using the run current line command along the way. You will also examine creating matrices and performing matrix operations in R; creating factors and data frames in R; performing data frame operations in R; and how to create and use a data frame.
11 videos | 56m
has Assessment available Badge
Importing & Exporting Data using R
An essential skill for statistical computing and graphics. The programming language R the tool of choice for data science professionals in every industry and field—both to take advantage of R's great graphic and charting capabilities and to create reproducible high-quality analyses. In this 8-video Skillsoft Aspire course, you will discover how to use R to import and export tabular data in CSV (comma-separated values), Excel, and HTML format. The key concepts covered in this course include how to read data from a CSV formatted text file and from an Excel spreadsheet; how to read tabular data from an HTML file; and how to export tabular data from R to a CSV file and to an Excel spreadsheet. In addition, learners will explore exporting tabular data from R to an HTML table; how to read data from an HTML table and export to CSV; and how to confirm that the contents of the CSV file were written correctly.
8 videos | 36m
has Assessment available Badge
Data Exploration using R
The tool of choice for data science professionals in every modern industry and field, the programming language R has become an essential skill for statistical computing and graphics. It both creates reproducible high-quality analyses and takes advantage of superior graphic and charting capabilities. In this 10-video Skillsoft Aspire course, you will explore data in R by using the dplyr library, including working with tabular data, piping data, mutating data, summarizing data, combining datasets, and grouping data. Key concepts covered in this course include using the dplyr library to load data frames; selecting subsets of data by using dplyr; and how to filter tabular data using dplyr. You will also learn to perform multiple operations by using the pipe operator; how to create new columns with the mutate method; and how to summarize data using summary functions. Next, use the dplyr join functions to combine data. Then learn how to use the group by method from the dplyr library, and how to query data with various dplyr library functions.
10 videos | 44m
has Assessment available Badge
R Regression Methods
The programming language has become an essential skill for statistical computing and graphics, the tool of choice for data science professionals in every industry and field. R creates reproducible high-quality analyses, and allows users to take advantage of its great graphic and charting capabilities. In this 8-video Skillsoft Aspire course, you will discover how to apply regression methods to data science problems by using R. Key concepts covered in this course include preparing a data set before creating a linear regression model how to create a linear regression model with the lm method in R; and extracting statistical results of a linear regression problem. You will also learn how to test the predict method on perform the preparatory steps needed to create a logistic model; and how to apply the generalized linear model (glm) method on a logistic regression problem. Finally, learners see how to create a linear regression model and use the predict method on a linear model.
8 videos | 39m
has Assessment available Badge
R Classification & Clustering
Explore the advantages of the programming language R in this 8-video Skillsoft Aspire course. An essential skill for statistical computing and graphics, R is the tool of choice for data science professionals in every industry and field. It both creates reproducible high-quality analyses, and offers unparalleled graphic and charting capabilities. Learners will examine how to apply classification and clustering methods to data science problems by using R. Key concepts covered in this course include performing the preparatory steps needed to create a classification and decision tree; using the rpart library and ctree library to build a decision tree; and how to perform the preparatory steps needed to carry out clustering. Next, explore use of the k-means clustering method; using hierarchical clustering with the hclust and cutree methods; and applying a decision tree method to a classification problem. Finally, learn to train a decision tree classifier by using the data and a relationship inside of those data.
8 videos | 41m
has Assessment available Badge
R for Data Science: Data Visualization
Continue exploring the advantageous aspects of the programming language R in this 8-video Skillsoft Aspire course. An essential skill for statistical computing and graphics, R has become the tool of choice for data science professionals in every industry and field. Learn how to create reproducible high-quality analyses, while taking advantage of R's great graphic and charting capabilities. Learners will explore how to use R to create plots and charts of data. Key concepts covered in this course include creating a scatter plot by using the built-in R method; creating a line graph on a time series data set; and creating a bar chart with the built-in R function bar plot. You will learn how to create a box and whisker plot by using the built in mtcars data set; to create a histogram with the built-in R function hist, and the equivalent by using the ggplot2 library functions; and how to create a bubble plot with the ggplot2 library. Finally, learn how to use an appropriate plot to visualize data.
8 videos | 35m
has Assessment available Badge
Cleaning Data in R
R is a programming language that is essential for data science, used for statistical computing and graphics. In this 13-video course, learners explore essential methods for wrangling and cleaning data with R. Begin by recognizing types of unclean data and criteria for ensuring data quality. First, learners see how to fetch a JSON (JavaScript Object Notation) document over HTTP and load data into a dplyr table. Learn how to load multiple sheets from an Excel document and how to handle common errors encountered when reading CSV (comma-separated values) data. Read data from a relational database with a SQL (structured query language) query. Explore joining tabular data by combining two related data sets by using a join operation, and spreading data—reshaping tabular data by spreading values from rows to columns. Look at summarizing data, applying a summary function using dplyr; imputing data, using mean imputation to replace missing values; and extracting matches, using a regular expression and data wrangling tools from the tidyverse package. The closing exercise practices data wrangling functions using R.
13 videos | 1h 7m
has Assessment available Badge
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BOOKS INCLUDED

Book

R in Action: Data Analysis and Graphics with R, Second Edition
Focusing on practical solutions, this book offers a crash course in statistics and covers elegant methods for dealing with messy and incomplete data that are difficult to analyze using traditional methods.
Book Duration 9h 19m
Book Authors By Robert Kabacoff

Book

Learn RStudio IDE: Quick, Effective, and Productive Data Science
For programmers who want to start doing data science, but don’t know what tools to focus on, this book is a quick, no-nonsense tutorial of RStudio that will give you a head start to develop the insights you need in your data science projects.
Book Duration 1h 18m
Book Authors By Matthew Campbell

Book

Advanced R Statistical Programming and Data Models: Analysis, Machine Learning, and Visualization
Including case studies throughout, this book shows you how to conduct data analysis using the popular R language.
Book Duration 7h 32m
Book Authors By Joshua F. Wiley, Matt Wiley

Book