| Call Number | 15406 |
|---|---|
| Day & Time Location |
S 4:30pm-6:20pm 417 Mathematics Building |
| Points | 3 |
| Grading Mode | Standard |
| Approvals Required | None |
| Instructor | Konstantin Kuchenmeister |
| Type | LECTURE |
| Method of Instruction | In-Person |
| Course Description | Generative AI (“GenAI") is reshaping the global economy and the future of work by revolutionizing problem-solving, optimizing complex systems, and enabling data-driven decision-making. Its profound impact spans across natural language understanding, image generation, and predictive analytics, marking a paradigm shift that necessitates a deep and rigorous understanding of its mathematical foundations. This course is designed to equip students with a comprehensive framework for exploring the mathematical principles underpinning GenAI. Emphasizing statistical modeling, optimization, and computational techniques, the curriculum provides the essential tools to develop and analyze cutting-edge generative models. |
| Web Site | Vergil |
| Department | Mathematics |
| Enrollment | 25 students (60 max) as of 10:06AM Thursday, October 30, 2025 |
| Subject | Mathematics |
| Number | GR5470 |
| Section | 001 |
| Division | Interfaculty |
| Note | MAFN Students ONLY. Open to STATS 1/10. Open to Univ. 1/18 |
| Section key | 20251MATH5470G001 |