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Most participants watch the videos at 1.5x speed. Course Overview: A data science course focused on analyzing and filtering grid reinforcement options for energy systems. Prerequisites: None Duration: 1 hour, 57 minutes Course Description: The course teaches how data science is used in the datasets of energy companies with information about grid reinforcement. For example, these datasets include information about the construction of new power lines, new substations, new storage units, new power stations, and combinations of such investments. Out of a large dataset of candidate reinforcement alternatives, learn how data science is applied to narrow down to fewer such alternatives. This smaller set of candidate reinforcements is then given as input to an optimization model. The solutions are compared using Python (you will learn how).