CMSC498Z

Selected Topics in Computer Science; Differentiable Programming

Reviews for this courseTestudo

Prerequisite: Minimum grade of C- in CMSC330 and CMSC351 This course is an introduction to differentiable Programming, a new programming paradigm in which a numerical program can be differentiated through automatic differentiation, allowing gradient-based optimization of parameters in the program. It has broad applications in Computer Graphics, Computer Vision, Deep Learning, Quantum Computing, System Control, and many more. The course assumes a good working knowledge of linear algebra and differentiation.

Sister Courses: CMSC498A, CMSC498B, CMSC498C, CMSC498D, CMSC498E, CMSC498F, CMSC498G, CMSC498I, CMSC498J, CMSC498K, CMSC498L, CMSC498N, CMSC498O, CMSC498P, CMSC498Q, CMSC498R, CMSC498T, CMSC498V, CMSC498W, CMSC498X, CMSC498Y

Fall 2025

Ming Lin

0 reviews
Average rating: N/A

Past Semesters

Ming Lin

0 reviews
Average rating: N/A

Ming Lin

0 reviews
Average rating: N/A

Ashok Agrawala

0 reviews
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 3.85 between 22 students*

CMSC498Z Grade Distribution+-051015202530354045505560657075808590% of studentsABCDFWother
A-: 22.73%
A: 54.55%
A+: 9.09%
B: 4.55%
B+: 4.55%
other: 4.55%
* "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.