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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.
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