Optimization: Fundamentals and Applications

CT Score

1500

#0 of 0 in AMATH

Difficulty

—/10

Workload

—h/wk

Median grade

from grade distribution

Would take again

—

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Grade distribution

Student-reported · course feedback surveys

48.5%

45.5%

6.1%

A-

By professor: same course, different game

PROFESSORSCOREGRADEHRS/WKTERMS

Aleksandr Aravkin

3 community ratings

7.6

——

Professor ratings →

Sections

No section data for this term yet.

In the tree

Proficiency in linear algebra and advanced calculus/analysis; recommended: Strongly recommended: probability and statistics. Desirable: optimization, e.g. Math 408, and scientific programming experience in Matlab, Julia or Python. Offered: jointly with IND E 515/MATH 515→AMATH 515→unlocks 3 courses

3 mapped courses list AMATH 515 as a prerequisite. See on the map →

Study groups

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