Covers the fundamentals of data science, emphasizing breadth over depth and practical application in machine learning and data analysis.
Covers the fundamentals of data science, the scientific method evolution, the role of a data scientist, and the significance of data as the new oil.
Explores the use of visual extensions, such as virtual reality and augmented reality, in enhancing workplace efficiency and communication.
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.
