Keyword: «python programming language»

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.

Due to the introduction of the discipline "Introduction to Modern Information and Intellectual Technologies" into the curricula of medical universities, which includes a section devoted to the basic principles and algorithms of machine learning and artificial intelligence (AI), there is a need to develop appropriate methodological support. The relevance of the research topic is due to the fact that the vast majority of medical students do not have the necessary knowledge in mathematics and programming, which are the theoretical foundations of modern intelligent technologies. This can lead to incorrect interpretation of AI-generated results in their future professional work. Therefore, it is important to consider the specific needs of this category of students when developing teaching materials. The aim of the article is to describe the authors' proposed approach to implementing computer experiments in the laboratory practice of the above-mentioned discipline, which allows students to gain a deeper understanding of the essence of the studied machine learning methods and the conditions for their application. The research methods used include classification methods used in machine learning, experimental design methods, and two-factor analysis of variance, which serves as a basis for evaluating the effectiveness of the proposed approach. The study was conducted with a participation of students from the Medical Institute of Mordovian University. The result is an approach developed by the authors for conducting laboratory work by medical students. This approach includes: studying the basic mathematical formulas underlying a particular machine learning method, performing simple computational tasks on a small amount of data, studying the basic functions of the Python language to implement a specific practical task, and conducting computer experiments to further explore the chosen mathematical model and improve its accuracy. The effectiveness of this approach has been confirmed by the results of a pedagogical experiment conducted by the authors. The theoretical significance of this work lies in the generalization and systematization of materials on this topic, and the results obtained complement existing scientific and pedagogical developments, deepening our understanding of the processes related to this topic, and they can be used in further research. The practical significance lies in the fact that the presented approach can be used as a basis for developing methodological materials on the topic "Machine Learning and Artificial Intelligence Technologies in Healthcare."

The article presents the features of developing a software solution in the form of a chat bot for Telegram, aimed at supporting people with diabetes in matters of self-monitoring their diet. Medical prerequisites for dieting are considered. The system architecture is described, including the use of the Python programming language and the Aiogram, SQLite and Matplotlib libraries. Algorithms for implementing the main functions and test results confirming the correct operation of the system are presented.