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.
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