<p>Lecture, three hours; discussion, one hour. Limited to Master of Applied Statistics and Data Science students. In-depth exploration of large language models (LLMs) and their applications in text mining. Students learn underlying architectures, techniques for fine-tuning and deploying these models, and how to leverage them for various text mining tasks. Through hands-on projects, students apply theoretical concepts to real-world datasets, enhancing their practical skills in the field. Letter grading.</p>

Statistics

College of Letters and Science

Statistics and Data Science

STATS 425 - Large Language Models in Text Mining

Large Language Models in Text Mining

Understand the architecture and training processes of large language models.

Fine-tune language models on specific datasets for improved performance.


Address ethical considerations and biases in the use of LLMs.

Apply pre-trained models for text mining tasks such as sentiment analysis, topic modeling, and information extraction.

Evaluate the effectiveness of different text mining techniques using large language

General Catalog

Large Language Models in Text Mining

STATS 425

4 units