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This lecture covers the concepts of linear estimation and prediction in the context of AR parametric models. It delves into topics such as the Yule Walker equations, Wiener filter, and Levinson's algorithm. The instructor explains the process of estimating parameters, minimizing mean square error, and predicting future values based on past observations.