Data Science For Dummies, 2nd Edition
- 10h 29m 1s
- Lillian Pierson
- Recorded Books, Inc.
- 2019
Jobs in data science abound, but few people have the data science skills needed to fill these increasingly important roles. Data Science for Dummies is the perfect starting point for IT professionals and students who want a quick primer on all areas of the expansive data science space. With a focus on business cases, the book explores topics in big data, data science, and data engineering, and how these three areas are combined to produce tremendous value. If you want to pick-up the skills you need to begin a new career or initiate a new project, listening to this book will help you understand what technologies, programming languages, and mathematical methods on which to focus.
While this book serves as a wildly fantastic guide through the broad, sometimes intimidating field of big data and data science, it is not an instruction manual for hands-on implementation.
In this Audiobook
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Chapter 1 - Wrapping Your Head around Data Science
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Chapter 2 - Exploring Data Engineering Pipelines and Infrastructure
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Chapter 3 - Applying Data-Driven Insights to Business and Industry
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Chapter 4 - Machine Learning—Learning from Data with Your Machine
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Chapter 5 - Math, Probability, and Statistical Modeling
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Chapter 6 - Using Clustering to Subdivide Data
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Chapter 7 - Modeling with Instances
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Chapter 8 - Building Models That Operate Internet-of-Things Devices
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Chapter 9 - Following the Principles of Data Visualization Design
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Chapter 10 - Using D3.js for Data Visualization
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Chapter 11 - Web-Based Applications for Visualization Design
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Chapter 12 - Exploring Best Practices in Dashboard Design
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Chapter 13 - Making Maps from Spatial Data
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Chapter 14 - Using Python for Data Science
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Chapter 15 - Using Open Source R for Data Science
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Chapter 16 - Using SQL in Data Science
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Chapter 17 - Doing Data Science with Excel and Knime
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Chapter 18 - Data Science in Journalism—Nailing down the Five Ws (and an H)
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Chapter 19 - Delving into Environmental Data Science
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Chapter 20 - Data Science for Driving Growth in E-Commerce
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Chapter 21 - Using Data Science to Describe and Predict Criminal Activity
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Chapter 22 - Ten Phenomenal Resources for Open Data
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Chapter 23 - Ten Free Data Science Tools and Applications
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