Healthcare Data Science Practicum

4.0 credits

This is a culminating experiential learning course where students will work in teams or individually on real-world data analytic challenges; Each student will prepare a final presentation and report documenting their work which will also serve as the culminating exam for the program; Students will work with real-world clinical data and implementable solutions for delivery to actual or potential stakeholders. The course will also introduce students to the process of how to structure a clinical question as a data science/machine learning problem, data acquisition/provenance, insight generation, and enable them to practice effective communication and storytelling to diverse stakeholders encountered in healthcare settings. Students will have the opportunity to work with datasets and problems originating from various areas within healthcare including bioinformatics/genomics, medical imaging, physiological signals and sensor data. Students can work with the course instructor to identify suitable project opportunities in collaboration with URMC clinical departments, research groups such as UR Health Lab and/or from their professional network/current place of work.