Introduces the basics of machine learning, covering supervised and unsupervised learning, linear regression, and data understanding.
Explores water consumption data in Geneva, including charts on consumption and losses, available datasets, and data processing phases.
Covers the analysis of air pollution data, focusing on R basics, visualizing time series, and creating summaries of pollutant concentrations.
Explores challenges in data assumptions, biases, and more in research, including incomplete write-ups and frustrations of newcomers.
