About
This course covers how to develop and test object-oriented programs for data science applications, including classification and approximation. Students learn to design simulations, determine algorithm complexity, test hypotheses, and evaluate reliability and validity. Topics include clustering, decision trees, graph optimization, histograms, linear regression, plotting, probability, and sampling.
Resources