Building a recommender system for school applicants for choosing speciality and elective courses from their curriculum using reinforcement learning algorithms
| dc.contributor.author | Serikbay A. | |
| dc.date.accessioned | 2025-04-02T06:17:01Z | |
| dc.date.available | 2025-04-02T06:17:01Z | |
| dc.date.issued | 2024 | |
| dc.description.abstract | Providing recommendations that are individualized and based on personal preferences has long been a challenge in the fields of academic guidance and career counseling in Kazakhstan. With an emphasis on prospective students, the system uses reinforcement learning algorithms to recommend electives and specialized courses that complement each school applicant’s distinct career interests. By using rigorous data gathering techniques and advanced recognition algorithms, the study not only reveals a new web application but also clarifies the complex process of assisting people in choosing satisfying career options. The study highlights its potential to improve academic performance as well as its practical value in increasing career counseling services through a series of trials, results, and discussions. The results have ramifications that go beyond the boundaries of conventional counseling. They provide insightful information for recommendation systems that assist recent grads in navigating the challenging terrain of employment options. This thesis is an excellent instance of innovation in the field of academic guidance because of its careful organization, which includes important chapters on the introduction to the research, the literature review, methodological nuances, architectural design, testing phases, and comparative analyses. By means of its academic contributions, it prepares the next generation of students starting their educational journeys with greater knowledge and agency. Keywords: Recommender system, School applicants, Elective courses, Reinforcement learning algorithms, Academic guidance, Web application. | |
| dc.identifier.citation | Serikbay A / Building a recommender system for school applicants for choosing speciality and elective courses from their curriculum using reinforcement learning algorithms / 2024 / Computer Science - 7M06102 | |
| dc.identifier.uri | https://repository.sdu.edu.kz/handle/123456789/1683 | |
| dc.language.iso | en | |
| dc.publisher | Faculty of Engineering and Natural Science | |
| dc.title | Building a recommender system for school applicants for choosing speciality and elective courses from their curriculum using reinforcement learning algorithms | |
| dc.type | Other |