Emne - Introduksjon til metoder for maskinlæring og kunstig intelligens med økonomiske anvendelser - IØ8812
IØ8812 - Introduksjon til metoder for maskinlæring og kunstig intelligens med økonomiske anvendelser
Om emnet
Nytt fra studieåret 2021/2022
Vurderingsordning
Vurderingsordning: Arbeider
Karakter: Bestått/ Ikke bestått
| Vurdering | Vekting | Varighet | Delkarakter | Hjelpemidler |
|---|---|---|---|---|
| Arbeider | 100/100 |
Faglig innhold
Introduction to machine learning and AI methods with economic applications 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 give an overview of machine learning methods within the AI framework. Economic applications for the learned methods will be presented and explored. The main goal is that students without previous knowledge in the area of machine learning and AI can understand and apply the models in their research topic. Examples of relevant applications are customer and marketing segmentation, credit risk assessment, forecasting and fraud detection.
Læringsutbytte
After having completed the course the candidate should be able to:
- explain and implement the different methods learned;
- choose the more suitable method 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
Anbefalte forkunnskaper
This course is designed for PhD candidates within the fields operations research, finance and economics. Programming skills are recommended.
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.
Ingen
Versjon: 1
Studiepoeng:
2.5 SP
Studienivå: Doktorgrads nivå
Termin nr.: 1
Undervises: HØST 2021
Undervisningsspråk: Engelsk
Sted: Trondheim
- Bedriftsøkonomi og optimering
- Bedriftsøkonomi
Ansvarlig enhet
Institutt for industriell økonomi og teknologiledelse
Eksamensinfo
Vurderingsordning: Arbeider
- Termin Statuskode Vurdering Vekting Hjelpemidler Dato Tid Eksamens- system Rom *
- Høst ORD Arbeider 100/100
-
Rom Bygning Antall kandidater
- * Skriftlig eksamen plasseres på rom 3 dager før eksamensdato. Hvis mer enn ett rom er oppgitt, finner du ditt rom på Studentweb.
For mer info om oppmelding til og gjennomføring av eksamen, se "Innsida - Eksamen"