For the attitude variable that did not change significantly, students' mean scores for attitude towards exposure to omics data analysis remained relatively consistent throughout the course (Wilcoxon Signed Rank test identified no statistically significant difference between pre-test (M= 3.61, SD= 3.42) and post-test (M= 3.42, SD=1.118; z=-1.50, p > 0.05). This indicates that this desire remained constant across the course. There were marginal differences in the attitude variable related to students' lack of confidence related to the use of Python; student's lack of confidence decreased significantly between pre-test (M=3.39, SD=1.22) and post-test (M=3.11, SD=1.079; z =-2.96, p > 0.01). This effect was relatively small in comparison to the other post-test measures, indicating that more exposure to python would help students further increase their confidence and perception of coding. Similar attitude trends are observed between the primary and secondary cohorts. We conducted a series of Wilcoxon Signed Rank tests that indicated significant changes to the students' attitudes toward omics after completing the full day intensive workshops. The attitude variables that stood out were significant improvements in students' understanding of and confidence with analyzing omics data after completing the workshop, with significantly large effect sizes (Table ). All attitude measures were found to increase significantly from pre-test to post-test except students' excitement to learn more about omics, which increased marginally, indicating the additional benefits of intensive workshops for encouraging marginalized students to engage with omics data (further research is needed to explore this trend). Importantly, there was a significant decrease in students' worries about Python and coding after completing the workshop, such that concerns decreased between pre-test (M=3.79, SD=1.188) and post-test (M=2.43, SD=1.222; z=-2.56, p <0.01). When asked three additional evaluative questions about the impact of the course at post-test, 75% or more of students in this cohort agreed that the course had improved their confidence in using omics data analysis (Table ).