Specialization Statistical Modeling for Data Science Applications

Statistical modeling is at the heart of data science. Well-designed statistical models allow data scientists to draw conclusions about the world based on the limited information contained in their data. In this three-credit sequence, students will add some intermediate and advanced statistical modeling techniques to their data science toolbox. Specifically, students will gain skills in the theory and application of linear regression analysis; ANOVA and experimental design; and generalized linear and additive models. Particular emphasis will be placed on analyzing real data using the R programming language. This specialization can be completed for credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) program, offered on Coursera. The MS-DS is an interdisciplinary degree that includes faculty from CU Boulder’s Applied Mathematics, Computer Science, Information Science, and other departments. Based on learning outcomes and requiring no application, the MS-DS program is ideal for individuals with broad educational and/or professional experience in computer science, information science, mathematics, and statistics.