Intelligent computing technologies in IT education: fractional, soft and quantum computing technologies and information complexity of finite objects

The article discusses the main definitions, provisions and principles of intelligent computing technology used in IT educational processes in the training of a new generation of specialists in the field of intelligent end-to-end IT and robotics for the implementation of a new direction of digital production Industry 4.0. The technology of intelligent computing is considered on the basis of three components: soft, fractional and quantum computing. The main features of the theory of soft computing and fuzzy systems in IT educational processes in combination with solutions to problems of theory and control systems are presented. The complicated points of fractional calculus and the theory of quantum algorithms for engineering are noted from the point of view of application in the design of intelligent control systems and cognitive robotics. The structures of genetic and quantum algorithms are compared. The results of the comparison allow to design new structures of hybrid quantum genetic algorithms. The combination of quantum genetic algorithms and quantum neural networks is the computational basis of quantum deep machine learning and forms a platform of quantum computational strong intelligence for cognitive robotics. The issues of choosing the type of intelligent computing for designing appropriate control algorithms depending on the computational and information measures of the complexity of the control object are discussed. Specific recommendations are given for the construction of educational programs for the training of new generation IT specialists for the design of robust intelligent control systems based on quantum end-to-end IT.