3 units
- Intelligent Systems
- Electives
- Core Requirements
- Advancement to Candidacy
- Intelligent Systems
Offered: Offered every term
Counts toward
- Artificial Intelligence and Technology, M.S. (2026-27) - Core Requirements
- Big Data Analytics, M.S. (2026-27) - Electives
- Big Data Analytics, M.S. (2025-26) - Electives
- Big Data Analytics, M.S. (2024-25) - Electives
Show all 10
- Computer Science, B.S. (2026-27) - Intelligent Systems
- Computer Science, B.S. (2025-26) - Intelligent Systems
- Computer Science, B.S. in Applied Arts and Sciences (2024-25) - Intelligent Systems
- Computer Science, M.S. (2026-27) - Advancement to Candidacy
- Computer Science, M.S. (2025-26) - Advancement to Candidacy
- Computer Science, M.S. (2024-25) - Advancement to Candidacy
Algorithms and computer methods for machine learning. Supervised methods: convolutional neural networks, feedforward neural networks, linear regression, logistic regression, support vector machine; unsupervised methods: dimensionality reduction, k-means clustering, subspace learning. Applications in classification, regression and visualization.
From the catalog
- Grading
- LTR: Letter Graded. The class will be offered for letter grade with no option to take it for Cr/NC
- Repeatable
- Maximum 3 units.
3 sections in Spring 2027
Class #6996· In-person · Open · Letter
65 of 65 seats open
Tue, Thu 5:30 PM-6:45 PM · P 144
Class #8993· In-person · Open · Letter
75 of 75 seats open
Tue, Thu 2:00 PM-3:15 PM · SSW 1500
Class #5906· In-person · Open · Letter
65 of 65 seats open
Tue, Thu 5:30 PM-6:45 PM · GMCS 324
To be Announced
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