Broad introduction to the principles behind image-based data. Aimed at graduate students actively working in research labs but assumes no prior experience with programming or any computational background beyond that of a typical PC/Mac user. Covers images generally but examples will be based on the types of images commonly used in biological research. Topics: Image fundamentals, Basic image processing, Image compression, Image storage and informatics, 3D and 4D data, Making accurate and optimal figures, Image integrity, Video, Quantification, Limits and confounds in analysis, automation of image processing and analysis. Lecture and computational exercises.