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Regular version of the site
Master 2023/2024

Modern Methods of Decision Making

Type: Compulsory course (Data Science)
Area of studies: Applied Mathematics and Informatics
When: 1 year, 3, 4 module
Mode of studies: offline
Open to: students of all HSE University campuses
Master’s programme: Data Science
Language: English
ECTS credits: 6
Contact hours: 60

Course Syllabus

Abstract

This course is a required foundational course for masters’ students in “Data Science” program, designed to familiarize them with the most recent methods of decision making. The course is divided into two parts. The first part tells about how a person makes decisions and covers the following topics: mathematical modelling, genetic algorithms, multi-criteria optimization. The second part of the course covers topic which explain how AI makes decisions or in more details how human makes decisions with a help of AI. The set of topics considered in this part of the course: multi-agent systems, prompt engineering, theoretical and informational foundations of machine learning.
Learning Objectives

Learning Objectives

  • The course gives students an important foundation to tackle real-life problems using classical applied math approaches as well as with a help of AI.
Expected Learning Outcomes

Expected Learning Outcomes

  • Learn how formulate a basic mathematical model for a problem presented in text form.
  • Learn some basic genetic algorithms and how to use the for solving optimization problems.
  • Learn main principals of prompt engineering
  • Learn how to formulate and solve basic multi-criteria optimization problem.
Course Contents

Course Contents

  • Mathematical modeling
  • Genetic algorithms
  • Multi-criteria optimization
  • Multi-agent systems
  • Prompt engineering
  • Theoretical and informational foundations of machine learning
Assessment Elements

Assessment Elements

  • non-blocking Лабораторная 1
  • non-blocking Лабораторная 2
  • non-blocking Коллоквиум 1
  • non-blocking Коллоквиум 2
Interim Assessment

Interim Assessment

  • 2023/2024 4th module
    Final = 0.25Л1 + 0.25Л2 + 0.25К1 + 0.25K2
Bibliography

Bibliography

Recommended Core Bibliography

  • Многокритериальные модели формирования и выбора вариантов систем, Дубов, Ю. А., 1986

Recommended Additional Bibliography

  • Современные алгоритмы поисковой оптимизации : алгоритмы , вдохновленные природой : учебное пособие, Карпенко, А. П., 2014

Authors

  • Антропова Лариса Ивановна