Keyword: «tabular information processing»

The modernization of higher education opens up prospects for the use of artificial intelligence (AI) in the training of specialists in the field of information technology, including those for the agricultural sector. Interaction supported by generative content services, in particular neural networks for working with tables, has the potential to improve the quality of student training. The aim of the study is to identify the specific aspects of the use of neural networks for working with tables in the training of IT specialists to improve its quality. The leading approach is modeling situations related to solving complex problems and developing innovative solutions for data analysis and processing. At the stage of assessing the quality of training of IT specialists, the materials of the control work including 50 questions (open and closed types) are used. The experimental work involves 64 students of the Russian State Agrarian University named after K. A. Timiryazev, studying in the field of training 09.03.02 Information systems and technologies, specialization "Computer science and data mining". Scientific novelty: the potential of including generative services for working with tables in the training of information technology specialists is substantiated. The results present the ideas of a methodological approach aimed at strengthening the influence of the identified factors to improve the quality of student training: the gradual, practical integration of AI elements into educational activities for the creation, processing of information and subsequent data analysis; the use of neural networks to work with tables at the hypothesis testing stage, compliance with information security rules. Theoretical significance – the identified didactic capabilities of neural networks for working with tables are clarified in relation to the training of students who are able to develop innovative solutions for data analysis, processing and protection. Practical significance – the factors influencing the effectiveness of the inclusion of neural networks for working with tables in the training of highly qualified personnel in the field of information systems and technologies have been identified. The results obtained are the basis for improving the training program for IT specialists and agricultural engineers. In conclusion, the specific features of using neural networks to work with tables are formulated: creating conditions for understanding the importance of the profession; combining theory and practice of information interaction; informing students about the limitations of using AI; accounting for cybersecurity issues.