STATISTICAL MODELS AND ALGORITHMS FOR DATA SCIENCE
The course is an intermediate level course in data science for students at the sophomore level with some experience in programming and background in mathematics (calculus). The course teaches students to “do” data science in Python using six modules to illustrate fundamental data science operations, data cleaning, model exploration, model formulation, model visualization, model communication. Recommended Prerequisite(s): COMP 182 .
Prerequisites & course information
Short Title: STATISTICAL MODELS FOR DS Department: Computer Science Grade Mode: Standard Letter Course Type: Lecture/Laboratory Credit Hours: 4 Restrictions: Enrollment is limited to Undergraduate, Undergraduate Professional or Visiting Undergraduate level students. Course Level: Undergraduate Upper-Level Prerequisite(s): COMP 140 and ( MATH 212 or MATH 222 or MATH 232 )
Sources
- Course catalogue ↗2026–2027