Data Science Foundations Tools and Techniques: Core Skills for Quantitative Analysis with R and Git (Addison-Wesley Data & Analytics Series)

The Foundational Hands-On Skills You Need to Dive into Data Science “Freeman and Ross have created the definitive resource for new and aspiring data scientists to learn foundational programming skills.” –From the foreword by Jared Lander, series editor 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. Learn to Install your complete data science environment, including R and RStudio Manage projects efficiently, from version tracking to documentation Host, manage, and collaborate on data science projects with GitHub Master R language fundamentals: syntax, programming concepts, and data structures Load, format, explore, and restructure data for successful analysis Interact with databases and web APIs Master key principles for visualizing data accurately and intuitively Produce engaging, interactive visualizations with ggplot and other R packages Transform analyses into sharable documents and sites with R Markdown Create interactive web data science applications with Shiny Collaborate smoothly as part of a data science team Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details. **The Foundational Hands-On Skills You Need to Dive into Data Science** > __“Freeman and Ross have created the definitive resource for new and aspiring data scientists to learn foundational programming skills.”__ > > –From the foreword by Jared Lander, series editor > > 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. Learn to * Install your complete data science environment, including R and RStudio * Manage projects efficiently, from version tracking to documentation * Host, manage, and collaborate on data science projects with GitHub * Master R language fundamentals: syntax, programming concepts, and data structures * Load, format, explore, and restructure data for successful analysis * Interact with databases and web APIs * Master key principles for visualizing data accurately and intuitively * Produce engaging, interactive visualizations with ggplot and other R packages * Transform analyses into sharable documents and sites with R Markdown * Create interactive web data science applications with Shiny * Collaborate smoothly as part of a data science team This unique guide brings together all the skills you need to get started with data science -- one of the world's fastest growing fields! Leading data science instructors Michael Freeman and Joel Ross start by guiding you through installing and configuring all the free open source software you'll need to solve professional-level data science problems. Next, they introduce key concepts, show how to work with data, and build your understanding with practical examples. You'll learn crucial R programming skills, and find easy-to-understand reference content to help you get the syntax right and troubleshoot your own code. Step by step, you'll learn through practical exercises that can be combined into complete data science projects. Everything's focused on practical application, so you can get real results, fast! Understand the field of data science (and why it's growing so fast) Install and configure R, RStudio, git, GitHub, and VSCode Keep track of your work with Git and GitHub Use simple Markdown code to style documents for easier understanding Work with the R programming language and its objects "Wrangle" data into shape for processing Create R visualizations with ggplot and Plotly Publish with RMarkdown Build interactive applications with Shiny And much more I 1 2 II 3 4 III 5 6 7 8 IV 9 10 11 12 13 14 V 15 16 17 VI 18 19 20 21