CS 468 - Introduction to Natural Language Processing with Deep Learning

Units: 3
Introduction to Natural Language Processing and Deep Learning. Topics such as Natural Language Processing tasks; Fundamental concepts of Deep Learning; Deep Learning models for Natural Language Processing; Large Language Models. Applications such as text classification, machine translation, text generation.

Prerequisites: STAT 316 and CS 311.
Possible Instructional Methods: On-ground, or Hybrid, or Online-Asynchronous, or Online-Synchronous.
Grading: A-F grading only.
Course Typically Offered: Fall & Spring

Student Learning Outcomes - Upon successful completion of this course students will be able to:

Describe fundamental concepts of deep learning and tasks of Natural Language Processing.
Explore different types of deep neural networks and basics of generative AI.
Build deep learning models for Natural Language Processing tasks such as text classification, machine translation.
Apply fine-turning and prompt engineering with pretrained large language models such as GPT models to natural language processing tasks.