SyllabusCourse informationAutumn 2015, Tuesdays 9:30am-11:30am Target audienceThis course is intended for graduate students in bioscience programs who want to develop programming skills using the MATLAB computing environment. No previous programming experience is required. Unregistered postdocs, RAs, etc. are welcome if space permits. Course summaryData analysis, visualization, and basic modeling techniques commonly encountered in biosciences research. Fundamentals of the MATLAB computing environment, programming and debugging, data import/export, data structures, plotting, image analysis, statistical tools. Examples and assignments will draw from a range of topics applicable to bioscience research, e.g. frequency analysis, genetic data mining, ion channel kinetics, neural spike rasters and spike-triggered averages, cell counting in fluorescence images, regression, PCA, and stochastic simulation. Assignments will be practical in nature and will demonstrate how to implement specific analyses that a biosciences student is likely to encounter. However, the skills taught are broadly applicable and specific knowledge of the examples covered is not necessary. CourseworkCoursework will consist of a weekly programming assignment that will be due at the beginning of the next class. Typically, the assignment description will be accompanied by helpful starter code. After an assignment is due, an example solution will be provided. We encourage you to read over the sample solution even if you were able to get everything to work on your own, as it will show best practices and useful extra tricks, tips, and MATLAB functions that we might not cover in class. A final project will allow students to work on a topic of their own choosing. Schedule
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