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Catalog Description
I 330M. Data Science Foundations for Biomedical Informatics. Learn fundamental data science skills for biomedical informatics, focusing on hands-on coding in Python and data analysis using Jupyter Notebooks. Gain experience with GitHub for project management and collaboration, explore topics like data visualization, Linux/Unix file systems, and Python programming. No prior coding experience required. Also offered as Informatics 320M.
Instructor Description
This course lays the foundation for data science education targeting health informatics students interested in learning more broadly about biomedical informatics. No previous coding experience is required. The students will be introduced to basic concepts and tools for data analysis. The focus is on hands-on practice and enjoyable learning. The course will use python as the programming language, and Jupyter Notebooks as the development environment (our “home base”) for the examples, tutorials, and assignments. We use Jupyterlab Notebooks because they are both the industry standard and a nice way to load, visualize, and analyze data and describe our findings in one environment. We will also learn GitHub to document changes and backup our work and, eventually, for use as a collaboration tool. Hands-on data analysis, final projects, and associated presentations will be mandatory for the completion of the course. The outcome for the class is that each student will have a GitHub repository with all of their work (Jupyter notebooks, data, etc.), including a final project that will be presented to the class. Specific topics to be covered include GitHub, Linux/Unix File system, Jupyter Notebooks, Python Programming, and Data Visualization.
Restricted to undergraduate Informatics majors through registration period 1. Informatics minors may add classes and join waitlists beginning in period 2. Outside students will be permitted to join our waitlists beginning with period 3.