Introductory course covering the foundations of computational imaging. Topics include basic image processing, convolutional neural networks for image processing, digital photography, inverse problems in imaging, proximal gradient methods, introduction to wave optics, time-of-flight imaging, and end-to-end optimization of optics and imaging systems. Emphasis on applications and solving inverse problems using classic algorithms, formal optimization, and modern machine learning techniques.