EECS 183. Natural Language Processing
Catalog Description: This course provides a hands-on introduction to language technologies, covering methods for processing speech and text. This includes: statistical models, early neural models, and transformer-based LLMs; model architectures, training, evaluation, and social impacts; core tasks and methods like machine translation, parsing, and prompting; analysis and representation of speech and speech recognition models. Weekly assignments provide practical experience in building systems and understanding their strengths and limitations.
Units: 4
Prerequisites: COMPSCI C182, COMPSCI 188, or COMPSCI 189
Credit Restrictions: Students will receive no credit for EECS 183 after completing COMPSCI 288. A deficient grade in EECS 183 may be removed by taking COMPSCI 288.
Formats:
Fall: 3.0 hours of lecture and 1.0 hours of discussion per week
Spring: 3.0 hours of lecture and 1.0 hours of discussion per week
Grading Basis: letter
Final Exam Status: Written final exam conducted during the scheduled final exam period
Class Schedule (Fall 2025):
EECS 183/283A – TuTh 15:30-16:59, Valley Life Sciences 2050 –
Alane Suhr, Gopala Krishna Anumanchipalli
Class Notes
FALL 2025 POLICY (Subject to change in future terms):
Phase 1 and 2 seats are open to EECS, CS, and non-EECS COE majors. Remaining seats open during the adjustment period.
*To enroll in this class, select the lecture and the 999 (placeholder) discussion section. Assignment to the actual sections will be managed by teaching staff.*
****PLEASE READ:
Required prerequisites: CS 182, 188, or 189. In Fall of 2025, we require that students have received at least an A- in at least one of these courses.
Required experience: basic familiarity with neural networks, e.g., past experience with Pytorch and numpy. We will not be providing introductory lectures or tutorials on the programming frameworks used in course assignments. Such experience may be acquired through deep learning assignments in CS 182, 188, or 189.****
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