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Getting Started with Data Science: Making Sense of Data with Analytics, 1st edition

Published by IBM Press (December 13, 2015) © 2016

  • Murtaza Haider

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Getting Started with Data Science takes its approach from worldwide best-sellers like Freakonomics and the books of Malcolm Gladwell: it teaches through a powerful narrative packed with unforgettable stories. The book covers basic theory and technique, backed with plenty of clear, jargon-free examples and practice opportunities. Everything's software and platform independent, so students can learn what they need whether they work with R, Stata, SPSS, SAS, or another toolset.

  • Teaches data analytics with the same popular approach that made Freakonomics and Malcolm Gladwell's books worldwide best-sellers
  • Covers crucial ingredients for practical success with data analytics -- especially how to create powerful, visual narratives to explain findings and make them actionable
  • Practical, hands-on, and product independent: supports any tool, application, or environment
  • Gives students extensive practice -- not just a single example for each concept
  • By an expert who has crafted 50+ of the world's most popular data analytics instructional videos
  • Chapter 1  The Bazaar of Storytellers    
  • Chapter 2  Data in the 24/7 Connected World   
  • Chapter 3  The Deliverable    
  • Chapter 4  Serving Tables   
  • Chapter 5  Graphic Details   
  • Chapter 6  Hypothetically Speaking      
  • Chapter 7  Why Tall Parents Don’t Have Even Taller Children        
  • Chapter 8  To Be or Not to Be    
  • Chapter 9  Categorically Speaking About Categorical Data       
  • Chapter 10  Spatial Data Analytics    
  • Chapter 11  Doing Serious Time with Time Series 
  • Chapter 12  Data Mining for Gold     
  • Index  
Murtaza Haider, Ph.D., is an Associate Professor at the Ted Rogers School of Management, Ryerson University, and the Director of a consulting firm Regionomics Inc. He is also a visiting research fellow at the Munk School of Global Affairs at the University of Toronto (2014-15). In addition, he is a senior research affiliate with the Canadian Network for Research on Terrorism, Security, and Society, and an adjunct professor of engineering at McGill University.
Haider specializes in applying analytics and statistical methods to find solutions for socioeconomic challenges. His research interests include analytics; data science; housing market dynamics; infrastructure, transportation, and urban planning; and human development in North America and South Asia. He is an avid blogger/data journalist and writes weekly for the Dawn newspaper and occasionally for the Huffington Post.
Haider holds a Masters in transport engineering and planning and a Ph.D. in Urban Systems Analysis from the University of Toronto.

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