Earners of this badge have completed a hands-on image processing module spanning classical computer vision and modern AI methods, applied to real environmental science images. Using Python in Google Colab with LLM-assisted coding, participants progressed from pixel-level image manipulation through threshold-based segmentation and morphological measurement, to YOLO deep learning object detection and segmentation, and finally to CNN and Random Forest image classification with data augmentation. Real-world datasets included oyster shell photographs from UMCES field collection and IFCB (Imaging FlowCytobot) phytoplankton images, grounding every technique in an applied environmental science context.