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Topics may include general techniques for making your figures accessible to a broad audience, learning to identify and fix common visualization errors in small sample size studies (bar graphs of continuous data, creating flow charts to track inclusion/exclusion, color blind accessible visualizations, using semi-transparency) and creating effective image-based figures (microscopy, electron microscopy, photographs, etc.). We will not address visualizations for big data, so attendees looking for this type of information might prefer to take another course.