Amid the climate crisis and rising energy costs, the need for improving energy efficiency is becoming increasingly critical. Governments aim to reduce carbon dioxide emissions, while businesses seek to optimize energy expenses. The digitalization of the energy sector and the adoption of Internet of Things (IoT) technologies create favorable conditions for the application of artificial intelligence (AI) in energy consumption management. This article provides an overview of AI technologies and their application in energy consumption management, using an ice rink as a case study. The energy consumption data collected from a real-world facility is analyzed, and methods of neural network modeling of time series for forecasting and optimizing management are examined. The results of the modeling are presented, demonstrating the potential of predictive algorithms in reducing energy costs and improving the operational efficiency of ice rinks.

Keywords: global warming, energy consumption, energy efficiency, digitalization, Internet of Things, artificial intelligence, energy management, machine learning, deep learning, time series, predictive algorithms

In order to provide information support for decision-making on the issuance of bank guarantees for the execution of a contract in the field of public procurement, it is important for banks to obtain historically accumulated information on the execution of government contracts. This is necessary to assess the possibility of the supplier's performance of his future contract. This can be done by collecting and aggregating information about contracts from the Unified Information System in the field of procurement. The paper proposes to use IT technologies and data analysis to predict the performance of the contract and identify bona fide suppliers. In the work, a selection of primary data on contracts was formed for modeling using the parsing of the FTP server of the Unified Information System in the field of procurement, and the parsed data was preprocessed for use in machine learning models.

Keywords: information system, data analysis, government contract, data parsing, machine learning

The article describes algorithms for constructing learning management system for the organization of individual student learning. This training takes place throughout training and is based on the multidisciplinary integration and internal differentiation. Also in the article describes the construction of such systems. We present an automated build environment of individual trajectories of student learning, developed by the authors and registered at the Federal Institute of Industrial Property, graphic model of the system, describes the algorithm proceeds and bonds, based on the theory of finite automata, the realization of the system design and implementation of the results in the learning process studentovdannoy system and the results of the implementation in the learning process of students.

Keywords: learning management system, the theory of finite automata, algorithms transitions, algorithms connections, automation training, individualized training, differentiated training

In the article the basic problems of the organization of teaching students the section "Programming" and the ways of solving these problems using developed by the authors of electronic educational resources, which is based on technology screencast. The results of using the resource in the educational process in the preparation of the students showed an increase of the level of formation of competence in the field of programming..

Keywords: a technique training to computer science, programming, expertise in programming, e-learning, the quality of education, electronic educational resources, technology, training, screencast, video screen, video capture