A Data Science Workshop (DSW) hosted at the University of Oklahoma Health Sciences Center (OUHSC) originated as a small gathering of local scientific computing specialists to share techniques and methods. However, as high-throughput data generation and AI/ML have gained prominence, there has been greatly increased demand from non-specialists, including PIs, postdoctoral fellows, and graduate students whose work mostly entails bench biology, for introductory and intermediate training in all aspects of data acquisition, storage, and analysis. They are generally computer-savvy already and able to program to some degree, and their interest is in short, hands-on demonstrations of how to apply AI/ML methods to data either generated or accessible via their research. The interest in data science classes is growing at OUHSC, but this need is still not met. Currently, the DSW is a volunteer effort, and the nascent OUHSC data science curriculum has minimal instruction on how to make data AI/ML ready or how to follow FAIR principles. This supplement will enable us to develop material on these topics and promulgate it via workshops, coursework, and freely accessible online content. Importantly, it will allow us to reach a much broader audience.