Programming Skills for Data Science brings together all the foundation skills needed to transform raw data into actionable insights for domains ranging from urban planning to precision medicine, even if you have no programming or data science experience.\n\nGuided by expert instructors Micheal Freeman and Joel Ross, this book will help learners install the tools required to solve professional-level data science problems, including widely used R language, RStudio integrated development environment, and Git version-control system. It explains how to wrangle data into a form where it can be easily used, analyzed, and visualized so others can see the patterns uncovered. Step by step, students will master powerful R programming techniques and troubleshooting skills for probing data in new ways, and at larger scales.\n\nSalient Features \n1. Guides students through setting up their computer for data science, understanding how the pieces fit together, and successfully using them to solve real problems \n2. Introduces R, RStudio, git, GitHub, Markdown, Shiny, and other leading tools \n3. Covers everything from preparing raw data to creating beautiful, sharable visualizations \n4. Anticipates questions and demystifies complex ideas, reflecting the authors' experience introducing data science to thousands of students"
Michael Freeman is an international photographer and writer based in London, who specializes in travel, architecture, and Asian art. He has been the principal photographer for the Smithsonian Magazine for many years, as well as working for Time Life Books, Reader's Digest, and the BBC. He has worked as either a photographer or writer on over 3 books, including Oriental Style (Thames & Hudson), Savouring India (Time Life Books), Japan Modern (Mitchell Beazley), The Spirit of Asia: Journeys to the Sacred Places of the East (Thames & Hudson), The Modern Japanese Garden (Mitchell Beazley), Ancient Angkor (Thames & Hudson), and Design Japan (Mitchell Beazley - published February 24).
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