Zoia V. Shilova

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.

Recently, Python programming has been introduced into the curricula for training specialists in many fields. This is due to the fact that the Python programming language has a wide range of options for use in various aspects (for example, it is convenient for web development, data analysis, writing scripts and games). Based on the analysis of practical activities, we can find that such a combination of options is not often needed by specialists in a particular field. Hence, there is a need to choose a priority when learning the Python programming language. The aim of the study is to examine the specific aspects of Python programming in the formation of students' digital competence. Scientific novelty: the necessity of choosing a priority direction of learning programming in Python for students of different areas of training is substantiated. The theoretical and practical significance lies in identifying the potential and characteristics of Python programming in the formation of digital competence among students of different areas of training. The presented article summarizes the experience and describes the results of a practical study aimed at justifying the specific aspects of teaching programming in Python to students of different areas of training. The criteria for the formation of digital competence of students who studied programming in 2020-2021 and in 2021-2022 academic years are given as the results of the control group. The results of the experimental group are considered to be the criteria for the formation of digital competence of students who studied programming in the 2022/2023 and 2023/2024 academic years. The conducted research has confirmed that teaching programming to students of different areas of training by choosing the priority direction of using the Python language is an effective means of forming their digital competence. The indicators of general cultural, general professional and professional competences are considered as criteria for the effectiveness of students' digital competence formation. The effectiveness of choosing a priority direction of programming in Python has been experimentally confirmed by the increase among the students of the experimental group of such professional indicators of students' digital competence as: the ability to apply theoretical knowledge and programming methods when working with non-standard professional tasks; the ability to select and use methods for complex solutions of professional tasks that have standard implementation conditions; the ability to work with HTML pages.