## 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**

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