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Machine Learning in Big Data Tasks Forecasting

Major: Software engineering
Code of Subject: 8.121.00.M.32
Credits: 4
Department: Publishing Information Technologies
Lecturer: Dr.Sc, Prof., Roman Tkachenko
Semester: 4 семестр
Mode of Study: денна
Learning outcomes:
• Ability to use advanced theoretical and fundamental knowledge to obtain predictive information in Big Data tasks.
• Ability to develop and implement predictive models of large information systems using computer simulation tools.
• Ability to efficiently perform system analysis, to choose conceptual model of information system environment based on predictive information models, including artificial intelligence.
• Ability to apply knowledge and practical skills of analysis of relevant regulations, current standards and technical specifications in the industry.
• Practical application of knowledge on the current state of affairs and the latest technologies of processing big data in the sphere of business, production, science.
• Teamwork skills and conflict resolution.
Required prior and related subjects:
Prerequisites:
• Big data management.
Сo-requisites:
• Control theory and optimal decision making.
Summary of the subject:
Basic concepts and definitions. One-step and multi-step forecasting. Basics of time series forecasting. Time series prediction methods. Computational intelligence and machine learning tools for forecasting tasks. Neural network prediction methods. GNM direct distribution for Big Data prediction. Features of machine learning of IC ICP for predicting random processes.
Recommended Books:
• В. Кулявець. Прогнозування соціально-економічних процесів / Кулявець В. О. – К. : Кондор, 2009. – 194 с.
• Про основні засади розвитку інформаційного суспільства в Україні на 2007– 2015 роки: Закон України від 9 січн. 2007 р. № 537– V. – Відомості Верховної Ради України. – 2007. –№ 12. – С. 102.
• Глущенко В. Прогнозирование / В.В. Глущенко В. В. – М. : Вузовская книга, 2005. – 205с.
Assessment methods and criteria:
performing tasks in practical classes (40%)
final control (exam): written-oral form (60%)