Course introduces undergraduate and graduate students to biomedical datasets, focusing on practical data parsing, visualization, and statistical analysis. Emphasis on developing coding skills in R and using omics, drug, and clinical data for analysis.
Additional Requirements for Graduate Students: Graduate students are expected to present projects based on thesis-relevant datasets.
Athena Title
Biomedical Data Literacy
Prerequisite
[(STAT 2000 or STAT 2000E) and (BIOL 1107 or BIOL 1107E or BIOL 2107H)] or permission of department
Semester Course Offered
Offered spring
Grading System
A - F (Traditional)
Student learning Outcomes
Students will increase awareness of biomedical datasets and associated software tools.
Students will develop skills in data parsing, visualization, and statistical analysis.
Students will apply statistical and coding skills to real-world biomedical data.
Students will understand and apply standard operating procedures within biomedical data research.
Students will understand categories of AI methods and capabilities as research tools.
Topical Outline
Introduction to Biomedical Datasets
Basic Skills in Omics, drug and clinical data analysis
