Prerequisites: Minimum grade of C- in CMSC330 and CMSC351 and permission of the CMNS-Computer Science department.

This course is an introduction to differentiable Programming, a new programiing 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. The course experience includes hands-on project s with differentiable programming for agentic AI systems and physical intelligence.