Teaching Data Analysis and Machine Learning at University: Generalization of Experience and Perspectives
The work substantiates the conclusion about the relevance of training professional personnel who can be involved in the implementation of the national project “Digital Technologies”, in particular, as specialists in the field of technologies related to data analysis, big data processing and machine...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | Russian |
| Published: |
The Fund for Promotion of Internet media, IT education, human development «League Internet Media»
2024-03-01
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| Series: | Современные информационные технологии и IT-образование |
| Subjects: | |
| Online Access: | https://sitito.cs.msu.ru/index.php/SITITO/article/view/1071 |
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| Summary: | The work substantiates the conclusion about the relevance of training professional personnel who can be involved in the implementation of the national project “Digital Technologies”, in particular, as specialists in the field of technologies related to data analysis, big data processing and machine learning. Obviously, it is especially important to study technologies related to data analysis, big data processing and machine learning for students of physics, mathematics and IT training. However, familiarity with the tasks that arise in data analysis leads to the idea that this section of computer science can be especially useful for students of natural sciences, medical fields of training, as well as sociologists, historians, psychologists, etc. This is determined by the accumulation of a significant amount of information on various applied tasks in the field of medicine, sociology, psychology, where it becomes possible to process and study data to study and predict the development of various situations. Taking into account the interdisciplinary focus of the applied problems under consideration, it becomes obvious that when mastering the relevant competencies, students will have to face serious problems in studying branches of science that are completely new to them. The article makes an attempt to systematize the experience of training students of the Federal State Budgetary Educational Institution of Higher Education "Oryol State University named after I.S. Turgenev" in data analysis and machine learning technologies, which was obtained over the past four years as part of training in basic and additional educational programs. The purpose of the research is to generalize the experience gained and find solutions to overcome difficulties associated with the development and modification of disciplines aimed at studying data analysis and machine learning technologies. The developed disciplines (modules) for studying data analysis and machine learning are demonstrated for students in various areas of training. It is noted that in order to fulfill modern tasks in the field of information technology, trained specialists need to have skills not only in programming, but also to be successful in analyzing interdisciplinary problems, which requires students to develop a broad outlook and the desire to obtain modern information. |
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| ISSN: | 2411-1473 |