Artificial intelligence and generative models

2025/2026

Учебный год

ENG

Обучение ведется на английском языке

3

Кредиты

Кто читает:

Департамент менеджмента

Статус:

Курс обязательный

Когда читается:

3-й курс, 2 модуль

Преподаватель

Терников Андрей Александрович

Course Syllabus

Abstract

Generative AI models use neural networks to identify patterns and structures in existing data and generate new, original content, allowing users to leverage the power of language. During this course, students will delve into the basics of generative AI models, exploring their definition, purpose, applications, and the key concepts that drive their success.

Learning Objectives

• Discover key concepts driving the success of AI technologies.
• Gain insights into generative AI models creating original content.

Expected Learning Outcomes

• OPK-2-Econ. Capable of gathering, organizing, and statistically examining the data essential to solving the specified economic challenges.
• OPK-5-Econ. Demonstrates proficiency in the utilization of contemporary information technologies and software tools for the resolution of professional tasks.
• PK-4-EconMan. Demonstrates proficiency in the areas of argumentation and data-driven decision making, exhibiting the capacity to articulate and justify management decisions with clarity and persuasiveness.
• PK-10-EconMan. Demonstrates a comprehensive understanding of the tools utilized in the field, including the ability to innovatively apply both novel and established technologies in industrial and research contexts.

Course Contents

• Introduction to Key Concepts in Generative AI
• Tools and Applications of Generative AI

Assessment Elements

• Tests
  Eight tests from the Online course organized via SmartLMS system (one test per each week in Online course). Each test of equal weight and of 10-points maximum. The final grade for all Tests is an average grade. Grade is not rounded.
• Seminars
  Seminars activities involving elements of ranking, teamwork, and game-based activities.
• Final Test
  Final Test from the Online course organized via SmartLMS system. 10-points maximum. Grade is not rounded.

Interim Assessment

• 2025/2026 2nd module
  0.7 * Final Test + 0.05 * Seminars + 0.25 * Tests

Bibliography

Recommended Core Bibliography

• Osondu, O. (2021). A First Course in Artificial Intelligence. Bentham Science Publishers Ltd.

Recommended Additional Bibliography

• Jason Bell. (2020). Machine Learning : Hands-On for Developers and Technical Professionals: Vol. Second edition. Wiley.

Authors

• Миронова Алена Геннадьевна
• Budko Viktoriia Aleksandrovna
• Ternikov Andrei Aleksandrovich