MATH 244 - Intermediate Data Science

Semester Offered: Fall or Spring
1 unit(s)

This course develops additional core skills and methods in data science, with a key focus on machine learning. We introduce the underlying mathematical and statistical theory, and apply the methods to an array of applications from different fields. Topics covered may include regression, clustering, classification, supervised and unsupervised machine learning, and non-standard data objects such as text data and network data. Students are expected to have statistical programming experience prior to this course.

Not open to students who have taken MATH 280 Intermediate Data Science or CMPU 250 Modeling, Simulation and Analysis .

The Department.

Prerequisite(s): MATH 240 and CMPU 100 , or permission of the instructor.

Three 50-minute periods.

Course Format: CLS