Foundations of Data Science for All
- Page ID
- 45152
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This book is a practical, beginner-friendly, interactive introduction to data science, designed for students with no programming experience and little background in math or statistics. Starting with the basics, the book gradually builds toward statistical analysis and introductory machine learning. As students read about each concept, they immediately put it into practice by running and experimenting with Python code within the book. This hands-on approach gives students experience with standard data science tools while learning to approach problems the way a data scientist does.
Front Matter
1: Introduction to Data Science
2: Numbers and Strings
3: Data Types
4: Sequences and Tables
5: Plotting
6: Table Manipulation
7: Conditionals, Iterations, and Probabilities
8: Sampling
9: Hypothesis Testing
10: Two-Sample Tests
11: Estimation
12: The Mean
13: Linear Regression
14: Root Mean Squared Error
15: Classification
16: Classifier
Back Matter
Thumbnail: Plexus net. (Unsplash License; Conny Schneider via Unsplash)


