The AI Methodology Map1 is a pedagogical tool that organizes and visualizes AI activities for digital methods-oriented research. By connecting concepts, technicity, and applications of generative methods, the map aims to assist scholars and students in becoming familiar with these methods through hands-on practice. This paper initially introduces an interactive visualization structured around five educational entry-points which revolve around questioning (1) the nature of generative methods under experimentation, including image, video, and audio generation, as well as understanding what is required for their use and critique. Additionally, these entry-points raise awareness about the essential (2) inputs and outputs of generative methods. They connect with existing tools, ready to be explored through (3) data practices and (4) documented in various ways. Consequently, the map prompts reflection on the (5) technicity of generative AI. Following this introduction, a case study demonstrates the application of the AI Methodology Map, utilizing a digital methodology to analyze various visual outputs generated by generative models. This case study specifically examines gender distinctions in the creation of image collections, and it is underpinned by a computer vision network approach. Finally, we critically reflect on current generative methods (using the map) simultaneously discussing the methodological potential of AI- generated image collections (as demonstrated in the case study).