Signals and Systems Principles for Data Scientists

A series of interactive, self-contained labs focused on key concepts from signals and systems theory tailored for data scientists, using real datasets and practical questions. The labs cover topics such as invertibility, causality, stability, Fourier analysis, frequency response, sampling, Laplace and z-transforms, emphasizing applications in data analysis and feature engineering.