Learning Data Science

Frontmatter

To the Data 100 Student
Prerequisites
Notation

The Data Science Lifecycle

1. The Data Science Lifecycle
2. Questions and Data Scope
3. Simulation and Data Design
4. Modeling with Summary Statistics
5. Case Study: Why is my Bus Always Late?

Rectangular Data

6. Working With Dataframes Using pandas
7. Working With Relations Using SQL

Understanding The Data

8. Wrangling Files
9. Wrangling Dataframes
10. Exploratory Data Analysis
11. Data Visualization
12. Case Study: Data Science for Accurate and Timely Air Quality Measurements

Other Data Sources

13. Working with Text
14. Web Technologies

Linear Modeling

15. Linear Models
16. Theory for Inference and Prediction
17. Loss, Risk, and Model Selection
18. Case Study: How to Weigh a Donkey

Classification

19. Classification
20. Gradient Descent and Numerical Optimization

Extra Topics

21. Replicable Research
- 21.1. P-hacking
22. Dimensionality Reduction and PCA
23. Decision Trees and Random Forests
24. Clustering

Appendices

Probability Review
Vector Space Review
Statistical Inference Review
- Hypothesis Testing and Confidence Intervals
- Permutation Test
Reference Tables
The Bias-Variance Tradeoff
Regularization
Contributors
References

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By Sam Lau, Joey Gonzalez, and Deb Nolan
© Copyright 2023.

License: CC BY-NC-ND 4.0