Includes bibliographical references and index.

I. Getting started. Setting up your computer
Using the command line
II. Managing projects. Version control with GIT and GitHub
Using Markdown for documentation
III. Foundational R skills. Introduction to R
Functions
Vectors
Lists
IV. Data wrangling. Understanding data
Data frames
Manipulating data with dplyr
Reshaping data with tidyr
Accessing databases
Accessing web APIs
V. Data visualization. Designing data visualizations
Creating visualizations with ggplot2
Interactive visualization in R
VI. Building and sharing application. Dynamic reports with R Markdown
Building interactive web applications with Shiny
Working collaboratively
Moving forward

"Using data science techniques, you can transform raw data into actionable insights for domains ranging from urban planning to precision medicine. Programming Skills for Data Science brings together all the foundational skills you need to get started, even if you have no programming or data science experience. Leading instructors Michael Freeman and Joel Ross guide you through installing and configuring the tools you need to solve professional-level data science problems, including the widely used R language and Git version-control system. They explain how to wrangle your data into a form where it can be easily used, analyzed, and visualized so others can see the patterns you've uncovered. Step by step, you'll master powerful R programming techniques and troubleshooting skills for probing data in new ways, and at larger scales. Freeman and Ross teach through practical examples and exercises that can be combined into complete data science projects. Everything's focused on real-world application, so you can quickly start analyzing your own data and getting answers you can act upon."--

Publisher's description

College of Engineering and Computer Studies Bachelor of Science in Information Technology

In English