AI 351 - Transformer Models and Large Language Models (LLMs)

3 Credit Hours

This course introduces transformer architectures and large-scale pre-trained models. Students study the mechanics of self-attention, positional encoding, and encoder-decoder architectures. The course emphasizes the development, fine-tuning, and deployment of models such as BERT, GPT, and T5. Ethical considerations and limitations of LLMs are discussed.
Corequisite: AI 332 - Deep Learning II: Sequential and Advanced Architectures (RNN, GRU, LSTM) (or a “C” or better)
Prerequisite: A “C” or better in:

AI 331 - Deep Learning I

AND AI 341 - Natural Language Processing

Lecture Hours: 3
Term(s) Offered: Spring