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PPOL 564 - Foundations of Data Science |

This critical first semester course aims to prepare all incoming students for the rigor of their upcoming coursework in the rest of the program. The course will accelerate the students to a level of mathematical and computer science competency that will enable them to excel in their ensuing data science courses. On the mathematical side, students will cover linear algebra with a special focus on matrix algebra (e.g. matrix notation, projections, determinants, inversions, and eigenvectors) and multivariate calculus up until constrained optimization. On the computer science side, students will be introduced to working at the command line and python programming, with introductions to data structures, data manipulation and programming paradigms. Students will work in notebooks and use Git/GitHub to submit coding assignments, developing literate programming and reproducible research skills they will use throughout the program. Professor Eric Dunford. For MS-DSPP students only. 3.000 Credit hours 3.000 Lecture hours 0.000 Lab hours Levels: MN or MC Graduate, Juris Doctor Schedule Types: Lecture, Seminar Public Policy Department Restrictions: Must be enrolled in one of the following Levels: Juris Doctor MN or MC Graduate Must be enrolled in one of the following Majors: Data Science for Public Policy |

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