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2025-2026 / MQGE9006-1

Forecasting and Microsimulation

Duration

30h Th

Number of credits

 Master in business engineering, professional focus in digital business5 crédits 
 Master in business engineering, professional focus in Financial Engineering5 crédits 
 Master in business engineering, professional focus in Financial Engineering (Digital Business - double diplomation avec la Faculté des Sciences Appliquées)5 crédits 
 Master in business engineering, professional focus in Intrapreneurship and Management of Innovation Projects5 crédits 
 Master in business engineering, professional focus in management and technologies (Industrial Business Engineering)5 crédits 
 Master in business engineering, professional focus in sustainable performance management5 crédits 
 Master in business engineering, professional focus in Supply Chain Management and Business Analytics5 crédits 
 Master in business engineering, professional focus in Supply Chain Management and Business Analytics (Digital Business - double diplomation avec la Faculté des Sciences Appliquées)5 crédits 
 Master in business engineering, professional focus in science and technology5 crédits 

Lecturer

Morgane Dumont

Language(s) of instruction

English language

Organisation and examination

Teaching in the second semester

Schedule

Schedule online

Units courses prerequisite and corequisite

Prerequisite or corequisite units are presented within each program

Learning unit contents

This course aims to equip students with conceptual and practical tools used to analyze, predict, and simulate the evolution of complex economic or social systems. The integration of forecasting techniques and microsimulation methods allows the course to explore short-term predictive analysis and long-term scenario evaluation, thereby supporting data-based decision-making in business, economics, and public policy.

Learning outcomes of the learning unit

By the end of the course, students will be able to:

  • Apply forecasting methods to real-world managerial and economic datasets.
  • Critically assess the performance and reliability of different forecasting models.
  • Design microsimulation models tailored to specific problems.
  • Combine predictive and simulation-based approaches to support strategic decision-making.

 

Prerequisite knowledge and skills

Basic statistics concepts, basics in excel and in any programming language (loops, variables, etc).

Planned learning activities and teaching methods

The course consists in face to face sessions including theory and applications. The students will need a computer for excel and RStudio.

Mode of delivery (face to face, distance learning, hybrid learning)

Face-to-face course

Course materials and recommended or required readings

Platform(s) used for course materials:
- LOL@


Further information:

Slides will be available on Lola and scientific articles will be recommended during the course.

Exam(s) in session

Any session

- In-person

oral exam

Written work / report


Further information:

During the semester, a project will have to be done by group. The aim of the project is to propose a scientific poster explaining a predetermined topic. The poster will be presented to the class during the last session. The poster + presentation will count for 50% of the final grade. Note that the participation to the project will be evaluated and the grade could be different for different member of the same group.

During the session, an oral exam containing theoretical and pratical questions will be organised individually. This exam will count for the 50% remaining of the final grade.

Work placement(s)

Organisational remarks and main changes to the course

Contacts

Main teacher : Morgane Dumont : morgane.dumont@uliege.be (office 3/7 in N1a)

Assistants : Emil Geleleens : Emil.Geleleens@uliege.be

                  Alexandre Kerff (check e-mail in the ULiege website)

Association of one or more MOOCs