Перегляд за Автор "Kravchuk, Olha"

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  • Ескіз
    Документ
    Programming basics: python for data processing
    (Хмельницький національний університет, 2025) Kravchuk, Olha
    The article discusses aspects of efficient data processing. Considerable attention is paid to the problems that arise in data modelling and forecasting. In today's digital world, data processing is becoming an essential skill in many professions, from business analytics to psychology. Today, almost every action leaves a digital footprint - online purchases, page views, answers to questionnaires, health indicators, GPS navigation, etc. This generates huge amounts of data that need to be processed, analysed, and used to make decisions. A special place in the paper is occupied by a description of the possibilities of software data processing using the Python programming language, which is becoming increasingly popular due to its simplicity, flexibility, open source, convenience of working with data in various formats, as well as many developed packages that facilitate fast and efficient information processing. NumPy, Pandas, which provide data structures and functions that make working with structured data simple and fast, the most popular data visualisation tool Matplotlib and Seaborn, they help to create graphs, charts and other visual representations of data, packages for various computational tasks SciPy, Statsmodels, and a machine learning-oriented package Scikit-learn which provides simple and effective tools for data analysis, it contains a variety of algorithms for classification, regression, and clustering. An example of using Python for data processing tasks is given. This example demonstrates how Python can be used to easily read data, perform basic statistical processing, and build visualisations, which is useful for psychological or sociological research. The paper contains an analysis of current scientific publications and identifies possible directions for future research.
  • Ескіз
    Документ
    Review and analysis of data processing information technologies in the course of modern computer science
    (Хмельницький національний університет, 2025) Kravchuk, Olha; Synyuk, Natalia; Kravchuk, Denys
    The article focuses on the review and analysis of data processing information technologies in the course of modern computer science. The article also presents theoretical aspects of such concepts as algorithms, data structures, computer architecture, logic, software, programming languages and concepts of their development, which have a significant impact on technological progress and social development, which, in turn, contribute to innovations in various fields, from medicine to finance, making life easier and improving working conditions, creating new business sectors and labor markets that meet the requirements of the digital economy, changing the way people communicate, educate and interact in society, in particular through the development of social networks and Internet platforms. Information technology has become not only the basis of modern computer science, but also a key determinant of technological progress and societal development. Understanding their role and interconnection helps to unlock the potential of these industries for further development and achievement of new heights in technology and innovation. Informatics, as the science of information processing, and information technologies that provide tools for this processing, form the basis for modern programming. They provide not only the necessary knowledge and tools, but also define strategies and methodologies for software development. Computer science covers many aspects, such as algorithms, data structures, computing theory, and much more. However, at the first stages of study, the basics of computer science usually include concepts such as algorithms, data structure, logic, computer architecture, programming languages, and software. They provide not only the necessary knowledge and tools, but also define strategies and methodologies for software development. Computer science covers many aspects, such as algorithms, data structures, computing theory, and much more. However, at the first stages of study, the basics of computer science usually include concepts such as algorithms, data structure, logic, computer architecture, programming languages, and software , which are discussed in this article
  • Документ
    Review and analysis of data processing information technologies in the course of modern computer science
    (Хмельницький національний університет, 2026) Kravchuk, Olha
    The article provides a comprehensive analysis of modern architectural approaches to software development using cloud technologies in the context of growing demands for scalability, fault tolerance, and security of information systems. It substantiates the relevance of the transition from traditional local deployment models to cloud environments that provide flexible resource management, elastic scaling, and cost optimization. It considers the evolution of cloud service delivery models (IaaS, PaaS, SaaS) and determines their impact on the formation of architectural solutions. Key architectural paradigms are analyzed, including monolithic, microservice, containerized, and serverless architectures. They are compared in terms of scalability, performance, fault tolerance, management complexity, and information security. Particular attention is paid to the role of containerization, resource orchestration, deployment automation, and the implementation of DevOps practices as important components of the modern cloud ecosystem. The paper proposes a generalized model for evaluating architectural approaches, which allows comparing technical characteristics with practical requirements for software systems of various scales and purposes. The conditions for the feasibility of each approach are determined depending on the specifics of the project, the predicted load, and resource constraints. The results of the study can be used in the design, modernization, and optimization of software systems in a cloud environment, as well as in scientific research aimed at developing architectural design methodologies in the context of digital transformation. further development of scientific research in the field of cloud architectures will contribute to improving the efficiency, reliability, and adaptability of modern software systems in the context of global digital transformation.