printer friendly pageMATH 104: Applied Matrix Theory
Linear algebra for applications in science and engineering: orthogonality, projections, spectral theory for symmetric matrices, the singular value decomposition, the QR decomposition, least-squares, the condition number of a matrix, algorithms for solving linear systems.
MATH 113 offers a more theoretical treatment of linear algebra.
MATH 104 and
ENGR 108 cover complementary topics in applied linear algebra. The focus of
MATH 104 is on algorithms and concepts; the focus of
ENGR 108 is on a few linear algebra concepts, and many applications. Prerequisites:
MATH 51 and programming experience on par with
CS 106.
Terms: Aut, Win, Spr, Sum
| Units: 3
| UG Reqs: GER:DB-Math, WAY-FR
Instructors:
Kim, G. (PI)
;
Ma, C. (PI)
;
Taylor, C. (PI)
;
Ying, L. (PI)
;
Diaconu, S. (TA)
;
Guijarro Ordonez, J. (TA)
;
Li, H. (TA)
;
Marsden, M. (TA)
;
Perlman, M. (TA)
;
Raksit, A. (TA)
;
Wu, Y. (TA)
MATH 113: Linear Algebra and Matrix Theory
Algebraic properties of matrices and their interpretation in geometric terms. The relationship between the algebraic and geometric points of view and matters fundamental to the study and solution of linear equations. Topics: linear equations, vector spaces, linear dependence, bases and coordinate systems; linear transformations and matrices; similarity; eigenvectors and eigenvalues; diagonalization. Includes an introduction to proof-writing. (
Math 104 offers a more application-oriented treatment.) Prerequisites:
Math 51
Terms: Aut, Win, Spr, Sum
| Units: 3
| UG Reqs: GER:DB-Math, WAY-FR
Instructors:
Varolgunes, U. (PI)
;
Venkatesh, S. (PI)
;
Vondrak, J. (PI)
...
more instructors for MATH 113 »
Instructors:
Varolgunes, U. (PI)
;
Venkatesh, S. (PI)
;
Vondrak, J. (PI)
;
Ye, L. (PI)
;
Dore, D. (TA)
;
Falcone, P. (TA)
;
Love, J. (TA)
;
Miagkov, K. (TA)
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