Why choose this course?

R is one of the most widely used data science tools worldwide, thanks to the power and flexibility it offers for statistical analysis and data visualization. This E-Learning training is designed to give you an in-depth understanding of R and take your skills as a data scientist to the next level.

This course will teach you essential techniques and workflows needed to be successful in data science, including:

• Data wrangling: Master techniques to clean, transform and prepare raw data for analysis.
• Debugging: Understand how to identify and fix errors in your R code.
• Defensive Programming: Learn techniques to write robust and error-resistant code.
• Domain-specific language integration: Learn how to integrate R with other tools and languages ​​for advanced data analysis.

This training provides a solid foundation for data scientists, with practical examples and exercises that you can immediately apply to your own projects.

Who should participate?

This course is ideal for:

• Beginning data scientists who want to learn how to work with R as their primary tool for data analysis and visualization.
• Statistics or analytics professionals looking to expand their skills with R.
• Academics and researchers who want to analyze and present their datasets using R.
• IT professionals who are involved in data-intensive projects and want to add R to their technical arsenal.
• Those interested in data science who want to understand how R can be used to generate valuable insights from data.

Course content

Data Wrangling in R

Course: 9 Minutes

• Course Introduction
• Introduction to Data Wrangling in R

The dplyr Library

Course: 52 Minutes

• Data Wrangling with dplyr
• Exploring Data with dplyr
• Filtering with dplyr
• Piping with dplyr
• Mutating Data with dplyr
• Summarizing Data with dplyr
• Selecting with dplyr
• Combining Data Sets with dplyr
• Set Operations with dplyr
• Arranging with dplyr

The tidyr Library

Course: 13 Minutes

• Data Manipulation with tidyr
• Gathering with tidyr
• Separating with tidyr

Rectangular Data Extraction

Course: 11 Minutes

• Using readr
• Using readxl

Practice: Using the dplyr Library

Course: 3 Minutes

• Exercise: Combine dplyr Verbs

Debugging

Course: 30 Minutes

• Course Introduction
• Debugging with RStudio
• Using Traceback
• Debugging with Browser
• Displaying Warnings and Messages
• Implementing Handlers
• Benchmarking in R

Defensive Programming in R

Course: 15 Minutes

• Methods of Defensive Programming
• Turning Warnings into Errors
• Programming with Asserts

Memory Management

Course: 9 Minutes

• Using pryr
• Addressing Memory with pryr

Practice: Using Debugging

Course: 2 Minutes

• Exercise: Debug with Browser

Utility Functions in R

Course: 33 Minutes

• Course Introduction
• Using substitute, quote, and deparse
• Using ast
• Using str
• Lazy Evaluation in R
• Using eval
• Using paste Functions

Classes and Operators

Course: 24 Minutes

• Creating Reference Classes
• Using class
• Defining a Binary Operator
• Simulating a Unary Operator

Code Translation

Course: 17 Minutes

• Using SQL to R Translation
• Exporting HTML tables
• Exporting a LaTeX document
• Using list2env

C and C++ Integration

Course: 15 Minutes

• Connecting inline C++ to R
• Calling External C++ with R
• Using cfunction in R

Practice: Code Transformation

Course: 3 Minutes

• Exercise: Output an R Table as LaTeX3

Library Tools

Course: 25 Minutes

• Course Introduction
• Exploring the tidyverse Collection of Libraries
• Manipulating Strings with the stringr Library
• Using the forcats Library
• Using the purrr Library

Web Application Tools

Course: 17 Minutes

• Creating a shiny Application
• Rendering a Plot in shiny
• Displaying a JavaScript DataTable

R Markdown

Course: 25 Minutes

• Using Markdown in R
• Rendering HTML
• Rendering LaTeX
• Passing knitr Parameters
• Referencing with bibtex

Practice: R Markdown Publishing

Course: 3 Minutes

• Exercise: Create and Publish from R Markdown

Start Data Science Using R today!

• Learn at your own pace with comprehensive interactive videos and exercises that guide you through the key concepts of data science with R.
• Instantly applicable knowledge to improve your data analysis skills and generate impactful insights.
• Become an R expert and grow your career opportunities in data science.

Order your course now and start your journey to data expertise today!