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This lecture covers the resolution of a system of linear equations using the least squares method, focusing on obtaining the matrix of coefficients and solving for the unknowns. It explains how to find the vector x that minimizes the difference between AX and b, even when there is no exact solution. The instructor demonstrates how to theoretically obtain the coefficient matrix and discusses practical approaches when b is obtained from experiments. The lecture emphasizes finding a vector that minimizes the error in the system, providing examples and methods to achieve this goal.