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

Also Offered As: EECS 283A

Prerequisites: COMPSCI C182, COMPSCI 188, or COMPSCI 189

Credit Restrictions: Students will receive no credit for EECS 283A after completing COMPSCI 288.

Formats:
Spring: 3.0 hours of lecture and 1.0 hours of discussion per week
Fall: 3.0 hours of lecture and 1.0 hours of discussion per week

Grading Basis: Default Letter Grade; P/NP Option

Final Exam Status: Yes

---

Class Schedule (Fall 2026):
EECS 183/283A – MoWe 15:30-16:59, The Gateway Building 1210 – Alane Suhr, Gopala Krishna Anumanchipalli

Class Notes
Phase 1 and 2 seats are open to EECS/CS Grad and EECS MEng students. Remaining seats open during the adjustment period for non-EECS Grads. Non-EECS MEng students are prevented from waitlisting or enrolling.


**Enrollment Permission seats are reserved for internal programs and are not open. Please DO NOT email the instructor or scheduling to request a seat**


*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.*

Links:

• EECS Course Archives (CalNet authentication required)
• CS enrollment policies
• EE enrollment policies
• HKN course maps