Data science: a first introduction

R and the tidyverse

Reading in data locally and from the Web

Cleaning and wrangling data

Effective data visualization

Classification I : training & predicting

Classification II : evaluation & tuning

Regression I : K-nearest neighbors

Regression II : linear regression

Clustering

Statistical inference

Combining code and text rwith Jupyter

Collaboration with version control

Setting up your computer.