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IØ8813

Advanced course in economic applications of machine learning and AI

Choose study year

Lessons are not given in the academic year 2024/2025

Credits 2.5
Level Doctoral degree level
Language of instruction English
Location Trondheim

About

About the course

Course content

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 within 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.

Learning outcome

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.

Learning methods and activities

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.

Compulsory assignments

  • Participation and compulsory activities

Required previous knowledge

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

Course materials

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

Subject areas

  • Managerial Economics, Finance and Operations Research
  • Business Economics

Contact information

Department with academic responsibility

Department of Industrial Economics and Technology Management