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Offers a comprehensive introduction to Data Science, covering Python, Numpy, Pandas, Matplotlib, and Scikit-learn, with a focus on practical exercises and collaborative work.
Covers the analysis framework for evaluating life cycle impacts, emphasizing climate change, environmental interventions, impact categories, and uncertainty in environmental data interpretation.
Explores the propagation of uncertainty in correlated variables and extreme correlations, Tchebychev inequality, confidence intervals, and Taylor series development.
