Covers dimensionality reduction, clustering, and density estimation techniques, including PCA, K-means, GMM, and Mean Shift.
Covers the essentials of data science, including data handling, visualization, and analysis, emphasizing practical skills and active engagement.
Covers the analysis of air pollution data, focusing on R basics, visualizing time series, and creating summaries of pollutant concentrations.
Explores parallel computation in CFD, emphasizing its implementation in Fluent and visualization techniques for scientific data interpretation.
Introduces the Applied Data Analysis course at EPFL, covering a broad range of data analysis topics and emphasizing continuous learning in data science.
