Publishing high-impact research in Psychology and Neuroscience and being competitive on the job market increasingly benefits from having mathematical and computational skills and using state-of-the-art data analysis and modeling methods. In a dialogue with recent studies in Psychology and Neuroscience, this course introduces key mathematical foundations including linear algebra, multivariable calculus, and probability theory, as well as applications such as linear models, dimensionality reduction, clustering, Bayesian models, and artificial neural networks. Along with the theory, the course will involve implementing the methods and models in Python. Throughout the semester, students will be encouraged to think about how to apply the contents of the course to their own research.
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