Data Science - A First Introduction

Data Science: A First Introduction focuses on using the R programming language in Jupyter notebooks to perform data manipulation and cleaning, create effective visualizations, and extract insights from data using classification, regression, clustering, and inference.The text emphasizes workflows that are clear, reproducible, and shareable, and includes coverage of the basics of version control. All source code is available online, demonstrating the use of good reproducible project workflows.Based on educational research and active learning principles, the book uses a modern approach to R and includes accompanying autograded Jupyter worksheets for interactive, self-directed learning. The book will leave readers well-prepared for data science projects.The book is designed for learners from all disciplines with minimal prior knowledge of mathematics and programming. The authors have honed the material through years of experience teaching thousands of undergraduates in the University of British Columbia's DSCI100: Introduction to Data Science course.

Product details

• Authors: Trevor Campbell, Campbell Trevor, Melissa Lee, Lee Melissa, Tiffany Timbers, Tiffany (University of British Columbia) Timbers, Tiffany-Anne Timbers, Tiffany-Anne (University of British Colum Timbers
• Publisher: Taylor & Francis Ltd.
• Languages: English
• Product format: Paperback / Softback
• Released: 30.04.2022
• EAN: 9780367524685
• ISBN: 978-0-367-52468-5
• No. of pages: 456
• Dimensions: 180 mm x 250 mm x 20 mm
• Series: Chapman & Hall/CRC Data Science Series
• Subjects: Natural sciences, medicine, IT, technology > Mathematics > Probability theory, stochastic theory, mathematical statistics; Artificial Intelligence, BUSINESS & ECONOMICS / Statistics, MATHEMATICS / Probability & Statistics / General, COMPUTERS / Machine Theory, environmental science, engineering & technology, Probability & statistics, Automatic control engineering, Databases, Probability and statistics, Environmental science, engineering and technology, COMPUTERS / Data Science / Data Analytics