Be able to formulate and improve an important research task, to solve it to collect the necessary information and to formulate conclusions that can be defended in a scientific context.
Use professional knowledge and practical skills to optimize the design of information systems of any complexity, to solve specific problems of designing intelligent information systems for the management of objects of different physical nature.
Be able to analyze and evaluate the range of tasks that contribute to the further development of effective use of information resources of decision-making systems.

Previous academic disciplines
Data mining
Methods and means of data integration
Decision theory
Related and subsequent disciplines
Project implementation process management
Data visualization
Machine learning

The purpose of teaching the discipline "Evolutionary Programming" is to study and practice the methods and algorithms of evolutionary programming, preparing students for the effective use of modern evolutionary methods for creation of automated systems in further professional activity; acquisition of practical skills in working with software tools for building intelligent models based on methods of evolutionary optimization.

1. Encyclopediaofartificialintelligence / Eds.: J. R. Dopico, J. D. delaCalle,A. P. Sierra. – NewYork :InformationScienceReference, 2009. – Vol. 1-3. – 1677 p.
2. Gen M. Geneticalgorithmsandengineeringdesign / M. Gen, R. Cheng. –NewJersey :JohnWiley&Sons, 1997. – 352 p.
3. Haupt R. Practicalgeneticalgorithms / R. Haupt, S. Haupt. – NewJersey :JohnWiley&Sons,2004. – 261 p.
4. Емельянов В. В. Теория и практика эволюционного моделирования /В. В. Емельянов, В. В. Курейчик, В. М. Курейчик. – М. :Физматлит, 2003. – 432 с.
5. Курейчик В. М. Генетические алгоритмы: монография /В. М. Курейчик. – Таганрог : ТРТУ, 1998. – 242 с.

40 points - laboratory work
60 points - exam

Be able to formulate and improve an important research task, to solve it to collect the necessary information and to formulate conclusions that can be defended in a scientific context.
Use professional knowledge and practical skills to optimize the design of information systems of any complexity, to solve specific problems of designing intelligent information systems for the management of objects of different physical nature.
Be able to analyze and evaluate the range of tasks that contribute to the further development of effective use of information resources of decision-making systems.

Previous academic disciplines
Data mining
Methods and means of data integration
Decision theory
Related and subsequent disciplines
Project implementation process management
Data visualization
Machine learning

The purpose of teaching the discipline "Evolutionary Programming" is to study and practice the methods and algorithms of evolutionary programming, preparing students for the effective use of modern evolutionary methods for creation of automated systems in further professional activity; acquisition of practical skills in working with software tools for building intelligent models based on methods of evolutionary optimization.

1. Encyclopediaofartificialintelligence / Eds.: J. R. Dopico, J. D. delaCalle,A. P. Sierra. – NewYork :InformationScienceReference, 2009. – Vol. 1-3. – 1677 p.
2. Gen M. Geneticalgorithmsandengineeringdesign / M. Gen, R. Cheng. –NewJersey :JohnWiley&Sons, 1997. – 352 p.
3. Haupt R. Practicalgeneticalgorithms / R. Haupt, S. Haupt. – NewJersey :JohnWiley&Sons,2004. – 261 p.
4. Емельянов В. В. Теория и практика эволюционного моделирования /В. В. Емельянов, В. В. Курейчик, В. М. Курейчик. – М. :Физматлит, 2003. – 432 с.
5. Курейчик В. М. Генетические алгоритмы: монография /В. М. Курейчик. – Таганрог : ТРТУ, 1998. – 242 с.

course work – 100