This lecture covers the basics of primal-dual optimization, focusing on minimax problems and the algorithms used to solve them. Topics include the minimax formulation, saddle points, gradient descent-ascent methods, and the performance of optimization algorithms. The instructor delves into the concepts of strong duality, Slater's condition, and the practical implications of these optimization techniques.