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Artificial Intelligence Machine Learning
Description: This course introduces data structures and algorithmic techniques as applied to artificial intelligence systems. Topics include array- and list-based representations, hashing and indexing, graphs, priority queues, and data structures supporting search, learning, and inference. Emphasis is placed on the impact of data organization on computational efficiency, scalability, and model behavior in AI applications. Letter grade only.
Units: 3
No sections currently offered.
Prerequisite: CS 136, AIML 136L. Corequisite: MAT 216
Artificial Intelligence Machine Learning
Term : Fall 2026
Catalog Year : 2026-2027
AIML 249 - Data Structure For Artificial Intelligence
Description: This course introduces data structures and algorithmic techniques as applied to artificial intelligence systems. Topics include array- and list-based representations, hashing and indexing, graphs, priority queues, and data structures supporting search, learning, and inference. Emphasis is placed on the impact of data organization on computational efficiency, scalability, and model behavior in AI applications. Letter grade only.
Units: 3
No sections currently offered.
Prerequisite: CS 136, AIML 136L. Corequisite: MAT 216