Over the course of this past summer, I worked with Professor Ryan J. Urbanowicz to complete 2 projects: the application of AutoMLPipe-BC, an automated ML pipeline designed for binary biomedical data classification, to the statistical analysis of a large-scale single nucleotide polymorphism (SNP) dataset with data collected from patients with congenital heart disease; and the creation of a novel, multi-class automated machine learning pipeline named AutoMLPipe-MC. Both of these projects required extensive data preprocessing and wrangling methods, an understanding of how to incorporate and update machine learning algorithms within AutoML pipelines, and the creation of relevant data visualizations to interpret the statistics generated by machine learning models.