STAT 1P50 - Introduction to Data Science

Topics may include basic programming skills in Python and Git; data collection and reading; data visualization; introductory statistical concepts; machine learning fundamentals; basics of regressions, decision trees, and neural networks; data ethics.

Course Format: Lecture, 3 hours per week; Lab/tutorial, 1 hour per week
Prerequisite(s): Grade 11 math or any university math credit or permission of the instructor
Course Notes: Designed for all first-year students, including but not limited to the Faculty of Mathematics and Science students. The course includes a final project. Major credit will not be granted to Mathematics majors. This course may be offered in multiple modes of delivery. The method of delivery will be listed on the academic timetable, in the applicable term.