Advanced Coding and Statistics for Biomedical Informatics
This course covers the programming, data analysis, and statistics skills required for advanced graduate-level courses in biomedical informatics. During the first half of the course, students develop coding skills to reproducibly analyze complex biomedical data. Topics include visualization, clustering, dimensionality reduction, and high-performance computing. During the second half of the course, students develop their statistical toolkit for robust hypothesis testing. Topics include hypothesis testing, parametric and non-parametric tests, simulations and resampling, regression models, classifiers, and statistical significance.
This course is highly interactive and applied. In-class activities and problem sets provide opportunities for students to practice analyzing real-world clinical, molecular, and epidemiological data to answer biological questions - from designing the analysis all the way through interpreting and communicating the results. All coding will be in the R programming language, so students should have basic R programming skills prior to enrolling in this course.
