COMPTNG 10C · PIC 10CAdvanced Programming
Program in Computing · 5 units · Undergraduate lower division (0-99)
More advanced algorithms and data structuring techniques; additional emphasis on algorithmic efficiency; advanced features of C++, such as inheritance and virtual functions; graph algorithms.
P/NP or letter grading.
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Checking the Schedule of Classes…
Requisites
Official UCLA wording
Enforced requisite: course 10B.
BruinTree reads · Prerequisite
confidence 1.00 · from textRequires
Everything that has to come before this course, not just the courses named in the requisite above.
COMPTNG 10C
- COMPTNG 10BIntermediate Programming
- COMPTNG 10AIntroduction to Programming
- COM SCI 31Introduction to Computer Science I
1 direct requisite. The whole upstream is here — 3 courses over 2 levels. Every course here opens its own tree.
Unlocks
What this course is a requisite for, and what those courses lead to in turn.
COMPTNG 10C
- COM SCI C121Probabilistic Models in Computational Genomics
- EC ENGR M146Introduction to Machine Learning
- STATS C163Generative Data Science
- EC ENGR C147ANeural Networks and Deep Learning
- EC ENGR C147BNeural Networks and Deep Learning II
- EC ENGR 201CArtificial Intelligence on Chip
- EC ENGR C247ANeural Networks and Deep Learning
- EC ENGR C247BNeural Networks and Deep Learning II
- LING 185AComputational Linguistics I
- COM SCI C122Algorithms in Computational Genomics
- COM SCI C124Machine Learning Applications in Genetics
- COM SCI 163Deep Learning for Computer Vision
- COM SCI 143Data Management Systems
- COM SCI 144Web Applications
- COM SCI 240ADatabases and Knowledge Bases
- COM SCI 240BAdvanced Data and Knowledge Bases
- COM SCI 241BPictorial and Multimedia Database Management
- COM SCI 245Big Data Analytics
- COM SCI 246Web Information Management
- COM SCI M146Introduction to Machine Learning
- COM SCI C160FFoundation Models: Principles and Practice
- COM SCI 162Natural Language Processing
- COM SCI 247Advanced Data Mining
- COM SCI C260FFoundation Models: Principles and Practice
- COM SCI 261Deep Generative Models
- COM SCI 168Computational Methods for Medical Imaging
- COM SCI C221Probabilistic Models in Computational Genomics
- COM SCI C222Algorithms in Computational Genomics
- COM SCI C224Machine Learning Applications in Genetics
- COM SCI 226Machine Learning in Computational Genomics
12 courses list this as a requisite. The whole downstream is here — 37 courses over 3 levels. Every course here opens its own tree.