MACHINE LEARNING
Machine learning is the process of automatically inferring a function from a set of data. In essence, machine learning techniques seek to automate the inductive learning process that humans do so well. Furthermore, the availability of large training sets combined with significant computing power has made machine learning an extremely important body of knowledge across a large range of application domains. A small sample of some of the application domains include robotics, medicine, speech/facial recognition, and driving autonomous vehicles. This course will focus on providing a foundational understanding of modern algorithms in machine learning, focusing on practical applications. Enrollment in online sections limited to students in the OMCS or OMDS programs. Enrollment in in person sections limited to students in the MCS or MDS programs. In order to enroll in an online section of this course, you are expected to have a working camera and microphone. During class sessions, you must be able to participate using your microphone and you are expected to have your camera on for the duration of the class so that you are visible to the instructor and other students in the class, just as you would be in an in-person class.
Prerequisites & course information
Short Title: MACHINE LEARNING Department: Computer Science Grade Mode: Standard Letter Course Type: Lecture Credit Hours: 3 Restrictions: Enrollment limited to students in the MCS, MDS, OMCS or OMDS programs. Enrollment is limited to Graduate level students. Course Level: Graduate Prerequisite(s): COMP 682 or COMP 614
Sources
- Course catalogue ↗2026–2027