Retrieval Augmented Generation System for Cyprus University of Technology Courses
Date Issued
May 2025
Author(s)
Advisor
Abstract
This thesis presents the design, implementation, and evaluation of a Retrieval Augmented
Generation (RAG) system specifically developed for Cyprus University of Technology
Computer Architecture course. The system aims to enhance students’ learning experience
by providing context-sensitive and accurate information retrieval from course materials.
By combining modern language models with a vector database of course content, the
system responds to student queries with precise information drawn directly from course
materials. Experiments demonstrate significant improvements in answer accuracy and
relevance compared to traditional search methods or standalone language models.
Generation (RAG) system specifically developed for Cyprus University of Technology
Computer Architecture course. The system aims to enhance students’ learning experience
by providing context-sensitive and accurate information retrieval from course materials.
By combining modern language models with a vector database of course content, the
system responds to student queries with precise information drawn directly from course
materials. Experiments demonstrate significant improvements in answer accuracy and
relevance compared to traditional search methods or standalone language models.
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