Courses

PATH 828, Bioinformatics for Cancer Research (Winter)

PATH 828 is a graduate course that I proposed, developed, and currently teach. It is designed for students with little computing background, but who are interested in developing computational and statistical skills for biomedical data analysis. The course covers the appropriate pre-processing and data analysis techniques for various genetic data types such as microarray, tissue microarrays, methylation, NanoString, RNAseq, miRNAseq, proteomics and qRT-PCR. Topics include basic programming in MATLAB, study design, applied statistics for clinical and genetic research, and machine learning approaches for data analysis. The course evaluation is based on four assignments, a paper critique and a course project. Each assignment is designed to address one of the main steps of data analysis. The skills that students obtain through these assignments are then applied to the course project.

Academic calendar: PATH 828 (PDF 60KB)

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PATH 411, Applied Data Science in Molecular Medicine (Fall)

Building upon the success of the PATH 828 graduate course, I expanded the undergraduate curriculum and developed an undergraduate course that teaches life-science and biomedical students statistical data analysis and experimental design. After completing this course, students should have a fundamental knowledge of programming, applied statistics, and machine learning. This will enable them to not only implement their own data analysis approaches but also better understand the analytical methods utilized in studies published in the literature, including advanced and innovative methods originating in the field of computational research.

Academic calendar: PATH 411

PATH 111, Data Science Through Visualization (Winter)

This blended course is designed to bring awareness and raise excitement in data science. Through different types of visualization students will learn key concepts of data science and big data investigation. The course will also explore examples of how data science is applied to solve problems in various disciplines.

Academic calendar: PATH 111