The Biomedical Machine Learning with Python course, hosted by cBLAST, offers a rigorous and application-driven exploration of machine learning techniques in the context of biomedical data. The course is designed for researchers, data scientists, clinicians, and students aiming to develop expertise at the interface of computational intelligence and biomedicine. It emphasizes algorithmic thinking, biomedical feature engineering, and ethical considerations in biomedical AI.

Learners will gain hands-on experience using Python’s scientific ecosystem—including libraries such as Scikit-learn, Pandas, NumPy, Seaborn, and TensorFlow/Keras—to implement and interpret machine learning models using real-world biomedical datasets, including gene expression profiles, electronic health records, diagnostic imaging features, and clinical trial data.