CMSC498P

Selected Topics in Computer Science; Machine Learning Capstone

Prerequisite: CMSC422 and permission of instructor. In this class, students will work either individually or in teams to complete a research or software development project involving machine learning or a closely related field. Students are encouraged to choose from a number of potential projects that will be proposed by tech companies, or else develop their own project with the approval of the instructor. Students are responsible for presenting the proposed project to the class and providing detailed documentation for the results of research. Grades will be assigned based on the quality of the project document, substance and quality of the project results, and feedback from project advisors.

Sister Courses: CMSC498A, CMSC498B, CMSC498C, CMSC498D, CMSC498E, CMSC498F, CMSC498G, CMSC498I, CMSC498J, CMSC498K, CMSC498L, CMSC498N, CMSC498O, CMSC498Q, CMSC498R, CMSC498T, CMSC498V, CMSC498W, CMSC498X, CMSC498Y, CMSC498Z

Past Semesters

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Average rating: N/A

During the Spring 2020 and Spring 2021 semesters, students could choose to take some of their courses pass-fail mid-semester which skews grade data aggregated across multiple semesters.

Average GPA of 2.95 between 13 students*

CMSC498P Grade Distribution+-05101520253035404550556065% of studentsABCDFWother
A: 61.54%
B: 7.69%
B+: 7.69%
F: 7.69%
W: 15.38%
* "W"s are considered to be 0.0 quality points. "Other" grades are not factored into GPA calculation. Grade data not guaranteed to be correct.