This course covers computational techniques for signal processing and weak signal detection in physics. Topics include Fourier transforms, filtering, power spectral density estimation, matched filtering, and introductory Bayesian methods. Students will develop tools to extract signals from noisy data and quantify the confidence of detection. Applications are drawn from gravitational wave detection, high-energy physics experiments, and cosmology. Emphasis is placed on practical data analysis and the construction of reliable, well-documented analysis pipelines for real or simulated datasets.