Machine Learning for Life Sciences

Catalog description

This course introduces machine learning (ML) concepts and practical applications within the life sciences. Students will learn supervised and unsupervised learning methods, feature selection, and model evaluation, using Python libraries such as scikit-learn, pandas, and seaborn to analyze biological, forensic, and biomedical datasets. Emphasis will be placed on understanding ethical implications, model interpretability, and reproducibility in computational biological research.