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The development and growth of the digital economy necessitates the acquisition and development of digital skills in the majority of the population. During the study, digital skills were divided into 4 levels: "digital literacy", "digital culture", "digital competence" and "digital professionalism". Considering the possible volumes of training and the contingent of students, the formation of such skills should be carried out in an electronic information and educational environment in a distance format. The aim of the study is to identify opportunities for the use of neural network technologies in the formation of digital skills in the remote format. The classification of neural network technologies is described, and a functional analysis is carried out. It was concluded that according to the results of questioning and input testing, neural network technologies automatically classify users according to levels: digital literacy, digital culture, digital competencies, or digital professionalism. Neural network clustering allows you to differentiate learning by identifying a learner in a particular cluster with a specific pace and content of learning. Neural network regression technologies reveal the most successful and most difficult areas of educational content and based on the identification of dependencies, individualized task pools are proposed. Neural network forecasting technologies allow us to design an individual trajectory of both training and further professional development, and based on the analysis of the Internet content of HR-services offers, possible vacancies are searched for and offered to those trained when profiles match.

The Use of Neural Network Technologies in the Electronic Information and Educational Environment in the Formation of Digital Skills