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This study is devoted to solving the problem of determining the career guidance of future university student using artificial intelligence systems. It is proposed Fully Connected Feed-Forward Neural Network (FNN) architecture and performed empirical modeling to create a Data Set. Model of artificial intelligence system allows evaluating the processes in an FNN during the execution of multi-label classification of professional areas. A method has been developed for the training process of a machine learning model, which reflects the internal connections between the components of an artificial intelligence system that allow it to “learn” from training data. To train the neural network, a data set of 29 input parameters and 23 output parameters was used; the amount of data in the set is 936 data lines. The software product was developed by Python and uses Keras, Numpy and Pandas libraries. Results of this research can be used to further improve the knowledge and skills necessary for successful professional realization.
Dolhopolov et al. (Thu,) studied this question.