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This lecture covers the basics of time complexity and Landau notation, focusing on understanding the concepts and their applications in algorithms. Starting with an introduction to the topic, the instructor explains the significance of analyzing the efficiency of algorithms. The lecture then delves into the details of different notations used to describe the complexity of algorithms, such as Big O, Omega, and Theta. Through examples and explanations, students learn how to analyze the time complexity of algorithms and make informed decisions about algorithm selection and optimization.