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Artificial Intelligence Machine Learning
Description: AIML 360 introduces the computational and statistical mathematical tools required for upper-division artificial intelligence coursework. The course serves as a core requirement for the Bachelor of Science in Artificial Intelligence and prepares students for subsequent courses in machine learning, deep learning, and AI theory. The emphasis is on using mathematics as a tool rather than on formal proofs. Students study linear algebra for representation, probability for modeling uncertainty, and calculus-based tools for optimization. Symbolic and numerical computation are used throughout to support computation, visualization, and interpretation. Letter grade only.
Units: 3
No sections currently offered.
Pre- or Corequisite: MAT 216, STA 270
Artificial Intelligence Machine Learning
Term : Fall 2026
Catalog Year : 2026-2027
AIML 360 - Computational And Statistical Tools For Artificial Intelligence
Description: AIML 360 introduces the computational and statistical mathematical tools required for upper-division artificial intelligence coursework. The course serves as a core requirement for the Bachelor of Science in Artificial Intelligence and prepares students for subsequent courses in machine learning, deep learning, and AI theory. The emphasis is on using mathematics as a tool rather than on formal proofs. Students study linear algebra for representation, probability for modeling uncertainty, and calculus-based tools for optimization. Symbolic and numerical computation are used throughout to support computation, visualization, and interpretation. Letter grade only.
Units: 3
No sections currently offered.
Pre- or Corequisite: MAT 216, STA 270