course-details-portlet

IØ8813 - Avansert kurs i økonomiske anvendelser av maskinlæring og kunstig intelligens

Om emnet

Undervises ikke studieåret 2024/2025

Faglig innhold

Advanced course in economic applications of machine learning and AI is an intensive PhD course offered through the project "COMPutational economics and optimization - Agents, Machines and Artificial intelligence" (COMPAMA). COMPAMA is developing an emerging interdisciplinary area in the borderland between economics, optimization, psychology, machine learning and AI with the main purpose to understand the economic impact of decisions, made by both machines and human agents.

This course will extend the knowledge in machine learning methods applied to economics, going beyond the traditional unsupervised and supervised methods. The main goal is that the students can understand and apply sophisticated models in economic applications. Examples of relevant applications are algorithmic trading, portfolio optimization and dynamic pricing. The main topic will be reinforcement learning.

Læringsutbytte

After having completed the course the candidate should be able to:

  • explain and implement the techniques learned;
  • choose the more suitable approach for a specific economic application;
  • recognize the opportunities and challenges of using AI in each context.

Læringsformer og aktiviteter

Lectures. Participation in the seminars is expected, which includes attendance at all lectures, as well as contributions to the discussions. There will be compulsory activities in the course.

Obligatoriske aktiviteter

  • Deltagelse og obligatoriske aktiviteter

Forkunnskapskrav

Admission to a PhD programme within operations research, or completed masters courses in optimization.

Kursmateriell

Selected literature. Will be given at course start-up.

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Versjon: 1
Studiepoeng:  2.5 SP
Studienivå: Doktorgrads nivå

Undervisning

Ingen

Undervisningsspråk: Engelsk

Sted: Trondheim

Fagområde(r)
  • Bedriftsøkonomi og optimering
  • Bedriftsøkonomi
Kontaktinformasjon

Eksamensinfo

  • * Skriftlig eksamen plasseres på rom 3 dager før eksamensdato. Hvis mer enn ett rom er oppgitt, finner du ditt rom på Studentweb.
Eksamensinfo

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