DATAC146

Students will build expertise in developing machine-learning tools to address challenges in health care. The course emphasizes both “how to formulate useful computational health problems”, and “how to develop computational solutions”. On the health side, we’ll get clinical guest lectures exploring challenges across diverse areas of healthcare (e.g., cardiology, cancer, primary care). On the computational side, the course will cover machine learning and deep learning foundations, state-of-the-art neural networks, and then advanced research topics. The course will emphasize rigorous evaluation, algorithmic bias, deployment, and auditing. The class will culminate in an open-ended final project, integrating skills learned in the course.

Alternative Final Assessment

Data C100 and Data C140

Course is not repeatable for credit.

Lecture