In 2019, we launched the teaching platform TeachOpenCADD on GitHub to help face these challenges (). TeachOpenCADD teaches by example how to build pipelines with open source resources used in the fields of cheminformatics and structural bioinformatics to answer central questions in computer-aided drug design (CADD). The code is written in Python, a popular programming language in many fields including computational life sciences. With these ready-to-use pipelines, we target students and teachers who need training material to CADD-related topics, as well as researchers who need a template or an inspiration to tackle their research questions. Usage can range from applying the December 8, 2021 whole pipeline on another molecular system to extracting selected pieces from the pipeline to be included in another context. The theoretical and practical aspects of each topic are covered in an interactive Jupyter notebook . This setup makes it easy for users from different fields to understand the computational concepts and to get started with hands-on Python programming. We call these Jupyter notebooks talktorials (talk + tutorial) because their format is suited for presentations as well.