High performance compute infrastructure has led to numerous breakthroughs and spurred increasing inclusion of bioinformatics approaches by researchers. For many academic scientists, computation is accomplished with local resources or those shared at partner institutes. Unfortunately, these systems become obsolete over time and due to high demand may have long job queues. Thus, there is a relentless need to modernize and expand computational resources. One potential solution is cloud computing where commercial systems for scalability. To prepare a biomedical workforce for this paradigm shifting in data science, NIGMS launched training modules in the NIGMS Sandbox for a variety of users to become competent in cloud computing. This proposal will expand these offerings to provide new modules specifically targeted to the undergraduate classroom. Their inclusion will expand the reach of NIGMS cloud training resources to very early career scientists and faculty who might not otherwise engage in cloud computing. To serve diverse interests, the modules will be available for artificial intelligence/machine learning (AI/ML), structural biology, and epidemiology research. The modules to be developed with this supplement will include lightweight datasets for exploring code. This will lead to minor compute time costs such that standard lab fees associated with a course will be sufficient to fund module activities. All modules will be designed to fit within up to five standard 150 minute class periods, giving faculty who adopt the curriculum the ability to include other topics in a semester. Thus, the modules can be worked into a variety of courses.