Data Science For Dummies (2016)
Part 1: Getting Started with Data Science
Chapter 1: Wrapping Your Head around Data Science
Chapter 2: Exploring Data Engineering Pipelines and Infrastructure
Chapter 3: Applying Data-Driven Insights to Business and Industry
Part 2: Using Data Science to Extract Meaning from Your Data
Chapter 4: Machine Learning: Learning from Data with Your Machine
Chapter 5: Math, Probability, and Statistical Modeling
Chapter 6: Using Clustering to Subdivide Data
Chapter 7: Modeling with Instances
Chapter 8: Building Models That Operate Internet-of-Things Devices
Part 3: Creating Data Visualizations That Clearly Communicate Meaning
Chapter 9: Following the Principles of Data Visualization Design
Chapter 10: Using D3.js for Data Visualization
Chapter 11: Web-Based Applications for Visualization Design
Chapter 12: Exploring Best Practices in Dashboard Design
Chapter 13: Making Maps from Spatial Data
Part 4: Computing for Data Science
Chapter 14: Using Python for Data Science
Chapter 15: Using Open Source R for Data Science
Chapter 16: Using SQL in Data Science
Chapter 17: Doing Data Science with Excel and Knime
Part 5: Applying Domain Expertise to Solve Real-World Problems Using Data Science
Chapter 18: Data Science in Journalism: Nailing Down the Five Ws (and an H)
Chapter 19: Delving into Environmental Data Science
Chapter 20: Data Science for Driving Growth in E-Commerce
Chapter 21: Using Data Science to Describe and Predict Criminal Activity
Part 6: The Part of Tens
Chapter 22: Ten Phenomenal Resources for Open Data
Chapter 23: Ten Free Data Science Tools and Applications