Computational and Inferential Thinking
UC Berkeley
The textbook of Data 8, UC Berkeley’s foundations of data science course, by Ani Adhikari, John DeNero and David Wagner. It teaches Python and working with tables alongside the core ideas of statistical inference: sampling, hypothesis testing, A/B testing, bootstrap confidence intervals, regression and classification. It relies on simulation more than formulas and assumes no background in programming or statistics.
What you'll learn
- Python and the datascience Tables library
- Visualizing data and using randomness and simulation
- Testing hypotheses and comparing two samples
- Estimating with bootstrap confidence intervals
- Prediction and inference with linear regression
- Classification with nearest neighbors
