This episodes presents methods for solving recurrence equations, which are crucial for analyzing the time complexity of recursive algorithms. It introduces asymptotic notations (Big O, Big Omega, Big Theta, little o, little omega) to describe the growth of functions. The lecture then explores several techniques for solving recurrences, including the substitution method, iteration method (and recursion trees), the Master Theorem, and solving homogeneous and non-homogeneous linear recurrences. Specific examples such as merge sort, binary search, and the Towers of Hanoi are used to illustrate these techniques. Finally, the limitations of the Master Theorem are discussed, along with strategies for handling cases where it is not applicable.