Computational Linear Algebra is a first-semester, first-year undergraduate course that shows how mathematics and computation are unified for reasoning about data and making discoveries about the world.
It was piloted in Fall-2020 by Jessy Grizzle, Maani Ghaffari, Tribhi Kathuria, Kira Biener, and Shaoxiong Yao.
Linear algebra and coding are rapidly becoming an essential foundation for the modern engineer in a computational world. Through this course, students gain insights into the mathematical theory of linear algebra and its realization in practical computational tools.
Math is the language of engineering, but coding is believing and realizing it. The mathematical content of ROB 101 is built around systems of linear equations, their representation as matrices, and numerical methods for their analysis. These methods are given life through the lens of robotics and contemporary intelligent systems and their compelling applications.
Math for Robotics
ROB 501
Applied mathematics for robotics engineers. Topics include vector spaces, orthogonal bases, projection theorem, least squares, matrix factorizations, Kalman filter and extensions, particle filters, underlying probabilistic concepts, norms, convergent sequences, contraction mappings, Newton Raphson algorithm, nonlinear constrained optimization, local vs global convergence, convexity, linear and quadratic programs, and randomized search strategies.
Class Notes: To request an override, a student must enter the waitlist and submit a request to the ROB Override System