University of California, Los Angeles 4 credits Education
(Formerly numbered 260B.) (Same as Public Policy M276B.) Lecture, three hours. Recommended requisite: course M260A. Second course in programming/data science sequence designed for students who do not have programming background. Uses primarily R programming language. Organized around practical programming skills/concepts that are fundamental across modern object-oriented programming languages (e.g., Python, Javascript). Topics include organizing files, folders, and scripts; reading (importing) and writing (exporting) data; using Git and GitHub for version control and collaboration; iteration (e.g., loops); conditional execution; writing functions; strings and regular expressions. These general programming skills are prerequisite for flashier data science applications (e.g., web-scraping, interactive maps). Students become proficient in programming skills/concepts through weekly problem sets, completed in groups. S/U or letter grading.
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