Confident Data Science
eBook - ePub

Confident Data Science

Discover the Essential Skills of Data Science

  1. 408 pages
  2. English
  3. ePUB (mobile friendly)
  4. Available on iOS & Android
eBook - ePub

Confident Data Science

Discover the Essential Skills of Data Science

About this book

The global data market is estimated to be worth $64 billion dollars, making it a more valuable resource than oil. But data is useless without the analysis, interpretation and innovations of data scientists. With Confident Data Science, learn the essential skills and build your confidence in this sector through key insights and practical tools for success. In this book, you will discover all of the skills you need to understand this discipline, from primers on the key analytic and visualization tools to tips for pitching to and working with clients. Adam Ross Nelson draws upon his expertise as a data science consultant and, as someone who made moved into the industry late in his career, to provide an overview of data science, including its key concepts, its history and the knowledge required to become a successful data scientist. Whether you are considering a career in this industry or simply looking to expand your knowledge, Confident Data Science is the essential guide to the world of data science. About the Confident series...
From coding and data science to cloud and cyber security, the Confident books are perfect for building your technical knowledge and enhancing your professional career.

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Yes, you can access Confident Data Science by Adam Ross Nelson in PDF and/or ePUB format, as well as other popular books in Languages & Linguistics & Careers. We have over one million books available in our catalogue for you to explore.

Information

Table of contents

  1. List of figures and tables
  2. About the author
  3. Preface
  4. Acknowledgements
  5. Links for the book
  6. 01 Introduction
  7. PART ONE Getting oriented
  8. 02 Genres and flavours of analysis
  9. 03 Ethics and data culture
  10. 04 Data science processes
  11. PART TWO Getting going
  12. 05 Data exploration
  13. 06 Data manipulation and preparation
  14. 07 Data science examples
  15. 08 A weekend crash course
  16. PART THREE Getting value
  17. 09 Data
  18. 10 Data visualization
  19. 11 Business values and clients
  20. Glossary
  21. Appendix A: Quick start with Jupyter Notebooks
  22. Appendix B: Quick start with Python
  23. Appendix C: Importing and installing packages
  24. List of data sources
  25. Notes
  26. Index