Students will learn how to build REST backend applications using ASP .NET Core to create, read, update and delete IoT data within relational (MS SQL with Entity Framework Core) and non-relations (MongoDB, CosmosDb, Redis) databases. By the end of the module, students will have the skills needed to create, configure, deploy, test and scale REST
Read MoreThis module provides an introduction to web interfaces development for Internet of Things (IoT) data visualization using ReactJS. Students will learn the fundamentals of ReactJS, including components, props, state, and lifecycle methods and how to create interactive user interfaces in form of responsive web applications. The course will also cover topics such as data visualization
Read MoreIntellectual systems learning module is designed to introduce students to the field of artificial intelligence and provide them with the foundational knowledge needed to design and implement intelligent systems. The module will cover a range of topics, including machine learning algorithms, natural language processing, computer vision, and intelligent agents. Students will learn how to use
Read MoreThe “Quality Assurance of IoT web-interfaces” module includes static and dynamic testing techniques, software automated testing approaches and patterns. Students will learn how to apply testing techniques to requirements’ testing, test cases’ writing and defect reports’ creating. They also will learn how to write GUI and API auto-tests from scratch. They will learn how to
Read MoreThe “UI/UX design in energy industry” module studies the theory and tools used in the development of applications and sites interfaces design. Students will learn practical methods of interfaces development and how to apply these techniques to energy-related data and sites. The module structure is built in a way to prepare students to the real
Read MoreThe “Design and development of information systems for energy industry control and monitoring” – main focus on the development of a information systems that can integrate data from various sources, such as sensors, meters, and other monitoring devices, to provide real-time information about energy usage and production. This could involve the use of advanced technologies
Read MoreThe module “Computer modelling and experiment design” is designed to study the methodology of computer simulation of models of objects and processes in the power industry and to study the methodology of planning a physical experiment to assess the adequacy of modelling. Students learn to simulate models of objects and processes in a specialized software
Read MoreThe “Principles and methods of data analysis in energy industry” module covers such topics as data collection methods, data preprocessing and data analysis techniques. Students will learn how to apply these techniques to energy-related data, such as energy consumption data, renewable energy generation data, or energy price data. By the end of the module, students
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