Natural Language Processing with Bag of Words & LLM Methods

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Further and more detailed information, including the schedule, can be found in the current course tables in the syllabus of the respective course, if the course is offered in the next sessions. The following text serves as information on what can be expected in terms of content in the course.

The Introduction to Natural Language Processing (NLP) at GSERM is a comprehensive journey into the world of textual data analysis. The course is designed to immerse attendees in both the theory and practical implementation of versatile NLP methods, transforming qualitative research prospects. Through a mix of lectures and labs, participants will gain practical proficiency in powerful NLP techniques that include: • Large Language Models (LLMs) • Prompt Engineering • Vector Database Basics • Bag-of-words Analysis • Sentiment Analysis • Document Classification and Clustering Students with previous experience in programming, graduate-level statistics, and mathematical theory will benefit most from this course. However, the curriculum is crafted to appeal and be accessible to all researchers eager to integrate NLP tools in their analysis.