2025/2026
Методы искусственного интеллекта в принятии решений
Статус:
Маго-лего
Где читается:
Факультет компьютерных наук
Когда читается:
1, 2 модуль
Охват аудитории:
для всех кампусов НИУ ВШЭ
Язык:
английский
Кредиты:
6
Контактные часы:
60
Course Syllabus
Abstract
The course is designed to provide a solid interdisciplinary foundation for understanding and developing advanced artificial intelligence (AI) systems. It combines modern mathematical methods, complex systems theory, and machine learning techniques, offering students a comprehensive understanding of modern decision-making processes.
Learning Objectives
- To develop students' fundamental understanding of the interdisciplinary principles (complexity theory, self-organization, and bifurcation) that underlie modern decision-making methods.
Expected Learning Outcomes
- Mastering the methods of complex systems analysis
- Mastering methods for determining power distributions
- Mastering numerical methods for solving ODEs, PDEs, and variational problems
- Mastering the method of bifurcation analysis of boundary value problems of ODEs and PDEs
- The ability to build a complete bifurcation picture of the PDEs
- Mastering methods of analyzing the complexity of systems
Course Contents
- Complex systems
- Bifurcation analysis of partial differential equations
- Complexity
- Self-organizing systems
