Explores autocorrelation, periodicity, and spurious correlations in time series data, emphasizing the importance of understanding underlying processes and cautioning against misinterpretation.
Covers correlation and cross-correlations in air pollution data analysis, including time series, autocorrelations, Fourier analysis, and power spectrum.
Explores the historical presence and effects of sulfur dioxide in the atmosphere, covering sources, impacts on health and the environment, emissions from metal smelters, and reduction strategies.
Explores advanced air quality modeling techniques to address health and climate issues, emphasizing the interconnectedness of air pollution and climate change.
Introduces atmospheric composition, focusing on geochemical cycles, atmospheric lifetimes, and the impacts of gases and aerosols on health and climate.
Introduces the Applied Data Analysis course at EPFL, covering a broad range of data analysis topics and emphasizing continuous learning in data science.
