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Books > Computing & IT > Computer programming > Programming languages
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Data Science Foundations Tools and Techniques - Core Skills for Quantitative Analysis with R and Git (Paperback)
Loot Price: R981
Discovery Miles 9 810
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Data Science Foundations Tools and Techniques - Core Skills for Quantitative Analysis with R and Git (Paperback)
Series: Addison-Wesley Data & Analytics Series
Expected to ship within 10 - 15 working days
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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.
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