- Materials for the book 'Probability and Statistics for Data Science' include a free preprint, 103 Python notebooks using 23 real-world datasets, 118 videos with slides, and solutions to 200 exercises.
- The book covers probability theory and statistics, focusing on topics like random variables, models, correlation, estimation, hypothesis testing, principal component analysis, and regression/classification methods, using real-world datasets to address challenges like overfitting and causal inference.
- Authored by Carlos Fernandez-Granda, an Associate Professor with 10 years of teaching experience, who provides learning advice and acknowledges contributors for typos and support from the National Science Foundation.