Vincent Granville Data Science Book

The Data Science book from Analytic Bridge founder Vincent Granville shows you what employers want and the skill set that separates the quality data scientist from other IT professionals.

Developing Analytic Talent, by Vincent Granville Developing Analytic Talent: Becoming a Data Scientist

By Vincent Granville
ISBN: 978-1-118-81008-8
336 pages, April 2014

This book is also part of Data Science Central apprenticeship and is available on Amazon and on Wiley website.

Data scientists are in demand, and this unique book shows you exactly what employers want and the skill set that separates the quality data scientist from other talented IT professionals. Data science involves extracting, creating, and processing data to turn it into business value. This guide discusses the essential skills, such as statistics and visualization techniques, and covers everything from analytical recipes and data science tricks to common job interview questions, sample resumes, and source code.

The applications are endless and varied: automatically detecting spam and plagiarism, optimizing bid prices in keyword advertising, identifying new molecules to fight cancer, assessing the risk of meteorite impact. This book:
  • Explains the finer points of data science, the required skills, and how to acquire them, including analytical recipes, standard rules, source code, and a dictionary of terms
  • Shows what companies are looking for and how the growing importance of big data has increased the demand for data scientists
  • Features job interview questions, sample resumes, salary surveys, and examples of job ads
  • Case studies explore how data science is used on Wall Street, in botnet detection, for online advertising, and in many other business-critical situations

  • Introduction xxi
  • Chapter 1 What Is Data Science? 1
  • Chapter 2 Big Data Is Different 41
  • Chapter 3 Becoming a Data Scientist 73
  • Chapter 4 Data Science Craftsmanship, Part I 109
  • Chapter 5 Data Science Craftsmanship, Part II 151
  • Chapter 6 Data Science Application Case Studies 195
  • Chapter 7 Launching Your New Data Science Career 255
  • Chapter 8 Data Science Resources 287
  • Index 299