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Магистратура 2026/2027

Искусственный интеллект в медиа

Статус: Курс обязательный (Современная журналистика)
Кто читает: Институт медиа
Когда читается: 2-й курс, 2, 3 модуль
Охват аудитории: для своего кампуса
Язык: английский
Кредиты: 6
Контактные часы: 64

Course Syllabus

Abstract

In this course, students will get a real picture of how artificial intelligence is already changing the economy and business. Instead of dry theory — case studies from major companies, current neural networks and bots that are working right now, and an honest conversation about what awaits the economy in the next 3–5 years. The course is designed to be engaging: minimal filler, maximum live examples, hands-on practice, memes, and real tools you can try out as soon as next week.
Learning Objectives

Learning Objectives

  • To provide current examples of the introduction of artificial intelligence in economics and finance
  • To introduce the basic neural network models and bots used in business
  • To train in the search for suitable artificial intelligence tools for a specific economic task
  • To present the limitations and risks of using artificial intelligence in the economy
  • To teach the specifics of analyzing real-world cases of artificial intelligence implementation
  • To inform about the trends in the development of artificial intelligence in the economy in the coming years
Expected Learning Outcomes

Expected Learning Outcomes

  • Understand how AI is already being applied in the economy and business, through concrete examples
  • Get a grasp of the current capabilities of neural networks and bots for solving economic problems
  • Learn to critically assess the prospects and risks of AI in the economy
  • Gain a practical understanding of the neural network market and tools of 2024–2026
Course Contents

Course Contents

  • Introduction and "AI is already here"
  • How AI trades on the stock exchange
  • Banks and AI
  • Amazon and dynamic pricing: why do prices change every few minutes?
  • Walmart and demand forecasting: how AI saves billions in warehouses
  • The Ant Financial (Alipay) case: credit scoring without a credit history
  • AI in retail
  • ChatGPT and analysts
  • Which neural networks exist in 2026
  • Economic bots
  • How neural networks work with tabular data
  • Generative AI in marketing and AI agents
  • Open vs. closed models
  • Risks and limitations of AI
  • The future: AI agents
  • Digital twins of the economy
  • New professions and disappearing roles
  • Ethics and regulation of AI
  • AI in business media
  • Final defense
Assessment Elements

Assessment Elements

  • non-blocking Attendance
  • non-blocking Activity in seminars
  • non-blocking Defense of the mini-project
Interim Assessment

Interim Assessment

  • 2026/2027 3rd module
    0.6 * Defense of the mini-project + 0.2 * Activity in seminars + 0.2 * Attendance
Bibliography

Bibliography

Recommended Core Bibliography

  • Artificial intelligence in economics and management, , 1987
  • Research handbook on intellectual property and artificial intelligence, , 2022

Recommended Additional Bibliography

  • Artificial intelligence and big data for financial risk management : intelligent applications, , 2023
  • Emotional AI : the rise of empathic media, McStay, A., 2018
  • Marx and the robots : networked production, AI and human labour, , 2022

Authors

  • Zelentsov Mikhail Vladimirovich