Computational Principles for High-dimensional Data Analysis

CT Score

1500

#0 of 0 in EECS

Difficulty

—/10

Workload

—h/wk

Median grade

A−

from grade distribution

Would take again

—

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Grade distribution

Student-reported · course feedback surveys

11.6%

32.6%

25.6%

27.9%

2.3%

A+

A-

B+

By professor: same course, different game

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In the tree

The following courses are recommended, undergraduate linear algebra (Math 110), statistics (Stat 134), and probability (EE126). Back-ground in signal processing (ELENG 123), optimization (ELENG C227T), machine learning (CS189/289), and computer vision (COMPSCI C280) may allow you to appreciate better certain aspects of the course material, but not necessary all at once. The course is open to senior undergraduates, with consent from the instructor.→EECS 208→unlocks 0 courses

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