Competitively oriented training approach of machine learning specialists

Abstract

Machine learning is of great interest in many ways as a practical tool for solving real problems arising in the production, financial sector, telecommunications, medicine and other fields of activity. However, at the moment there is a shortage and an urgent need for specialists in the field of Machine Learning (ML), who have competencies in both the field of applied mathematics and in the field of software development. The aim of the study is to develop a methodology for teaching machine learning tools using active learning practices through participation in competitions to analyze various data. As methods of forming the methodology, methods of active learning were used, based on the principles of problematics, adequacy, mutual learning, individualization, research of the problems and phenomena studied, immediacy and motivation. Using the proposed methodology in the form of a course (extra-curricular activities) allowed students to develop both professional competencies in the field of data analysis (the ability to process primary data; conduct preliminary data preparation for analysis, to use machine learning tools to solve problems of analyzing heterogeneous data), as well as social cultural competencies (knowledge of a foreign language in the field of data analysis, the ability to perceive new information, highlight the main goals and decomposition of task into subtasks, the ability to communicate and to work in a team, to produce new knowledge on their own, withstand the put time and qualitative framework for problem solving). As a result of the courses, according to the proposed methodology, specialists were trained who successfully solve practical problems in areas requiring the use of machine learning methods.