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This lecture covers the Karush Kuhn Tucker (KKT) conditions for optimization problems, introducing the concept of convex optimization. It explains the Farkas lemma and the relationship between different sets in optimization. The lecture delves into the definition of KKT points and the conditions for a point to be considered a KKT point. It also discusses the importance of constraint qualifications in optimization problems and the properties of convex sets. The presentation concludes with the concept of tangent cones of convex sets and their significance in optimization theory.