"The most comprehensive book I have seen for those wanting to get into data science - what <i>Harvard Business Review</i> called 'the sexiest job of the 21st century'."
Ben Taylor, Chief AI Evangelist, DataRobot
"<b>Kirill Eremenko's</b> book skilfully unravels the mysteries behind all the popular analytics tools and techniques, as well as many of the algorithms that power intelligent systems. I would recommend it to anyone who wants to pursue a career in data science.<i> </i>"
Dan Shiebler, Senior Machine Learning Engineer, Twitter Cortex
"<b>Kirill Eremenko</b> has come up with an amazing, unique way of making data science simple. From novices to the most experienced, anyone wanting to learn about data science will benefit from this book. Kirill covers everything from what data is and how to wrangle it, to helping you develop your own data analysis process, to effectively communicating with data. This book has it all!<i> </i>"
Andy Kriebel, Head Coach, The Information Lab Data School
"<b>Eremenko</b> is an established voice in the field, and his book is a must-read for anyone with an interest in using data science for business. Crammed with advice, <b><i>Confident Data Skills</i></b> provides the means to broaden one's horizons through data."
Michael Segala, CEO and Co-Founder, SFL Scientific
"Terrific. <b>Eremenko</b> has a knack for rendering complex theories in clear, elegant prose. Instructive and spirited, it will help you think - not only about the world around you but also about yourself."
Damian Mingle, Chief Data Scientist, Intermedix
- Chapter - 00: Introduction;
- Section - ONE: "What is it?" key principles;
- Chapter - 01: Defining data;
- Chapter - 02: How data fulfils our needs;
- Chapter - 03: AI and our Future;
- Section - TWO: "When and where can I get it?" data gathering and analysis;
- Chapter - 04: Identify the problem;
- Chapter - 05: Data preparation;
- Chapter - 06: Data analysis (part I);
- Chapter - 07: Data analysis (part II);
- Section - THREE: "How can I present it?" communicating data;
- Chapter - 08: Data visualization;
- Chapter - 09: Data presentation;
- Chapter - 10: Your career in data science