Data Mining

Major: Administration of Cybersecurity Systems
Code of subject: 7.125.04.O.001
Credits: 4.00
Department: Information Security
Lecturer: Khoma V.
Semester: 1 семестр
Mode of study: денна
Learning outcomes: 1. Communicate freely in national and foreign languages, orally and in writing, to present and discuss the results of research and innovation, ensure business/operational processes and issues of professional activity in the field of information security and/or cyber security. 2. Critically consider the problems of information security and/or cyber security, including at the interdisciplinary and interdisciplinary level, in particular on the basis of understanding the new results of engineering and physical and mathematical sciences, as well as the development of technologies for creating and using specialized software. 3. To analyze, develop and support the system of auditing and monitoring the effectiveness of the functioning of information systems and technologies, business/operational processes in the field of information and/or cyber security as a whole. 4. Make well-founded decisions on organizational and technical issues of information security and/or cyber security in complex and unpredictable conditions, including using modern methods and means of optimization, forecasting and decision-making. 5. Set and solve complex applied engineering and scientific problems of information security and/or cyber security, taking into account the requirements of domestic and international standards and best practices.
Required prior and related subjects: Computer methods of high-level design of protection devices Security systems of intelligent objects
Summary of the subject: Basic concepts in the field of intelligent data analysis. Statistical methods of data analysis. Correlation and regression analysis. Principles of intelligent data analysis. Solving the classification problem. Solving the classification problem. Solving the association problem. Neural networks and their learning algorithms. Use of fuzzy sets. Genetic algorithms.
Assessment methods and criteria: Current control of classroom classes is carried out with the aim of: • identifying the level of students' knowledge before starting classes; • ongoing verification of mastery of each studied topic; • assessment of the student's activity in the process of performing laboratory work; • verification of the execution and content of laboratory work reports; • inspection of control works. The final control is carried out based on the results of the test control and oral survey. Performing laboratory work and protecting reports (35) Performance of control works (15) Final semester control of learning the theoretical course (45 points written and 5 points oral components)
Recommended books: 1. Черняк О.І. Інтелектуальний аналіз даних: підручник. – К: Знання, 2014. –599с. 2. Луис Педро Коэльо, Вилли Ричарт. Построение систем машинного обучения на языке Python. 2-е издание / пер. с англ. Слинкин А. А. – М.: ДМК Пресс, 2016. – 302 с.: ил. 3. Плас Дж. Вандер. Python для сложных задач: наука о данных и машинное обучение. — СПб.: Питер, 2018. — 576 с.: ил.