EC ENGR C247B

Neural Networks and Deep Learning II

Electrical and Computer Engineering · 4 units · Graduate courses (200-299)

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Covers topics in deep learning including deep generative modeling, transformers, and deep reinforcement learning. Concurrently scheduled with course C147B.

S/U or letter grading.

Requisites

Official UCLA wording
Requisite: course C247A.

BruinTree reads · Prerequisite

confidence 1.00 · from UCLA’s structured data

EC ENGR C247A

Requires

Everything that has to come before this course, not just the courses named in the requisite above.

EC ENGR C247B

EC ENGR C247ANeural Networks and Deep Learning
- EC ENGR 131AProbability and Statistics
  - MATH 32BCalculus of Several Variables2 more beneath
  - MATH 33BDifferential Equations1 more beneath
- EC ENGR 133AApplied Numerical Computing
  - EC ENGR 131AProbability and Statisticsanother path to it
  - C&EE M20Introduction to Computer Programming with MATLAB
  - COM SCI 31Introduction to Computer Science I
  - MECH&AE M20Introduction to Computer Programming with MATLAB
- EC ENGR M146Introduction to Machine Learning
  - EC ENGR 131AProbability and Statisticsanother path to it
  - C&EE 110Introduction to Probability and Statistics for Engineers1 more beneath
  - COM SCI 32Introduction to Computer Science II
  - COMPTNG 10CAdvanced Programming1 more beneath
- EC ENGR 205AMatrix Analysis for Scientists and Engineers

1 direct requisite. Showing 19 courses over 3 levels; the branches marked with a count carry on past it. Every course here opens its own tree.

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What this course is a requisite for, and what those courses lead to in turn.

No course in the catalog lists this as a requisite.