Introduces the Applied Data Analysis course at EPFL, covering a broad range of data analysis topics and emphasizing continuous learning in data science.
Covers the essentials of data science, including data handling, visualization, and analysis, emphasizing practical skills and active engagement.
Delves into the 'digital turn' in history, examining historical research using digitized newspapers and exploring text reuse, word embeddings, and data visualization.
Covers the analysis of air pollution data, focusing on R basics, visualizing time series, and creating summaries of pollutant concentrations.
Introduces the basics of machine learning, covering supervised and unsupervised learning, linear regression, and data understanding.
Covers the fundamentals of data science, emphasizing breadth over depth and practical application in machine learning and data analysis.
Explores systemic environmental assessment, national material flow analysis, and urban metabolism dashboard development for Zurich using open data.
Covers the NABEL Data Analysis Assignment, emphasizing data analysis skills and report formatting for air pollution concentrations and meteorology.
Delves into data physicalization, expressiveness, feminist visualization, and the balance between exploration and explanation in data visualization.
