EC ENGR 205A · EE 205AMatrix Analysis for Scientists and Engineers
Electrical and Computer Engineering · 4 units · Graduate courses (200-299)
Designed for first-year graduate students in all branches of engineering, science, and related disciplines. Introduction to matrix theory and linear algebra, language in which virtually all of modern science and engineering is conducted. Review of matrices taught in undergraduate courses and introduction to graduate-level topics.
Letter grading.
When it runs
Checking the Schedule of Classes…
Requisites
Official UCLA wording
Preparation: one undergraduate linear algebra course.
BruinTree reads · Preparation
needs reviewconfidence 0.00 · from textBruinTree could not read this requirement — see UCLA’s wording above.
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Requires
Everything that has to come before this course, not just the courses named in the requisite above.
Nothing — this is an entry point.
Unlocks
What this course is a requisite for, and what those courses lead to in turn.
EC ENGR 205A
- EC ENGR C147ANeural Networks and Deep Learning
- EC ENGR C147BNeural Networks and Deep Learning II
- EC ENGR 201CArtificial Intelligence on Chip
- EC ENGR 210AAdaptation and Learning
- EC ENGR 210BInference over Networks
- EC ENGR C247ANeural Networks and Deep Learning
- EC ENGR C247BNeural Networks and Deep Learning II
3 courses list this as a requisite. The whole downstream is here — 7 courses over 2 levels. Every course here opens its own tree.