This lecture covers the Fast Fourier Transform (FFT) algorithm, including the review of practical aspects of Discrete Fourier Transform (DFT), interpolation formula, FFT in N dimensions, and examples from exercise sessions. The FFT algorithm is explained as a divide and conquer approach, with details on radix-2 FFT and its implementation. The lecture also delves into the application of FFT in image processing, filters, noise removal, and experimental techniques like Transmission Electron Microscopy (TEM) and Scanning Tunneling Microscopy (STM).