Data Science Methodologies in Biological and Health Sciences

Recommended preparation, BIOL 101 . This course integrates statistical and bioinformatics methodologies with data science techniques to analyze biological data. Students will learn statistical inference, predictive modeling, and machine learning approaches applied to biological datasets such as genomic, epigenomics, sequencing, and population genetics data. The course emphasizes hands-on experience with R, Python, and bioinformatics databases, preparing students to interpret complex biological data and make data-driven decisions in health informatics and biomedical research.