Course ObjectiveAcquiring skills and experience necessary for building decision support
systems, and learning to apply relevant scientific knowledge.
Specifically, during the course you will:
- select the appropriate scientific method(s) for the problem at hand
- implement and validate the scientific methods chosen
- build a user-friendly interface for potential users in the field
The programming language will be decided upon with your supervisor.
Common programming languages used during the project are Python, R, and
Course ContentProject optimization of business processes concerns the construction
and/or design of (part of) a decision support system (DSS) that:
- is designed and built in a scientifically sound way;
- can be used in practice.
The DSS is built in groups of students.
Method of AssessmentGrading for scientific quality, applicability, and verification of DSS,
plan, and final report. Individual grade for participation in group
based on observed participation and a short written or oral exam.
There is no resit. If the DSS and report are of sufficient quality, but
the individual contribution is insufficient by a small margin (max 1.0
pt), the student get the opportunity to hand in an additional assignment
to obtain a sufficient grade.
Target AudiencemBA, mBA-D
Additional InformationImportant note: you are expected to attend the kick-off meeting. If (due
to circumstances) you are not able to attend this meeting, you should
notify the lecturer well in advance. Failing to do so may exclude you
Recommended background knowledgeApplied Stochastic Modeling (X_400392).
|Language of Tuition||English|
|Faculty||Faculty of Science|
|Course Coordinator||dr. R. Bekker|
|Examiner||prof. dr. G.M. Koole|
You need to register for this course yourself
Last-minute registration is available for this course.
|Teaching Methods||Lecture, Practical|
This course is also available as: