Available To: all qualified students, see placement requirement link on the Science Department page or the Computer Science & Engineering page

Schedule: one semester

Special Notes: This course does not count towards the diploma requirement for the Science department. Students taking this course must simultaneously be enrolled in a year of traditional science or have successfully completed three years of traditional science.

Data literacy is increasingly important in our world. This course combines the vital arenas of statistical knowledge and programming skills with the purpose of analyzing and visualizing the past, as well as predicting the future. The course content will address common applications in a variety of domains including science, finance, business, and sports, and will give students the skills and analytical tools necessary to learn from data efficiently and make informed decisions. The curriculum includes descriptive statistics, an overview of Python, Jupyter notebooks, an introduction to Pandas, data visualizations, exploratory data analysis, ethical issues, and predictive analytics. The prerequisite is Introduction to Computer Science, Introduction to Programming, or its equivalent.