CSIS 185
Computational Theory for Al
Grossmont College · UGRD · Fall 2026
Catalog description
This course covers the mathematical foundations of artificial intelligence, focusing on applied matrix theory using TensorFlow, optimization via gradient algorithms, and Bayesian methods for pattern recognition and decision-making. Students will learn to implement and optimize AI models, applying these techniques to real-world problems in AI. (CSU/UC)
Sections
Current meeting, instructor, credit, and enrollment details
0468
19 openSeats: 7/26 seats Last recorded: Aug 13, 2026, 3:58 PM- Days & times
- Mo · 2:00 – 4:20 PM
- Meeting dates
- Aug 24 – Dec 21
- Location
- Bldg 70 113; Distance Education/Online WEB
- Instructor
- Nuzen, A
Section notes
Section 0468 is a hybrid course that will require both on-campus and online meetings. Scheduled meeting times are noted above. TBA/TBD = To be announced/determined and will be offered asynchronously (WEB). Familiarity with computers, Internet required. For more information, email the instructor. [https://www.gcccd.edu/staffdirectory/search.asp] *ZTC* Zero Textbook Cost section: This course does not require purchase of a textbook and may use free Open Educational Resources (OER) or free textbook alternatives.