Business Decisions Modeling using Machine Learning, Econometric Modelling and Explainable Artificial Intelligence 2400-ENSM090B
The seminar is designed for students who are committed to working systematically throughout the academic year and, above all, are prepared to make the effort required to produce a high-quality master’s thesis.
During the seminar, selected issues related to business decision modelling will be discussed. These issues will be connected to the students’ thesis topics.
In the first semester, each student will be required to present and discuss a selected academic article relevant to their planned master’s thesis. In the second part of the semester, each student will prepare a presentation of the preliminary results of their research.
In the second semester, each student will be required to present the final results of their research.
The seminar will be completed in the third semester, following the preparation and submission of a high-quality master’s thesis.
The estimated student workload is 12 contact hours for seminar classes, 18 contact hours for preparing the master’s thesis, and 45 hours of independent work. The total estimated workload is 75 hours.
The estimated student workload:
Type of activity K (contact) S (self-learning)
seminar (clasess) 12 0
Thesis preparation 18 45
Total 30 45 = 75
Course coordinators
Type of course
Learning outcomes
Knowledge:
1. The student knows the rules of writing a master thesis.
2. The student knows methods of analyzing data and methods of research
3. The student knows basics of methodology of science and ways of formulating scientific hypotheses.
4. The student knows basic definitions connected to hard to measure phenomena.
5. The student has basic knowledge regarding quantitative methods used in research on hard to measure phenomena.
Skills:
1. The student is capable of finding data and information necessary for preparing a master thesis. The student is able to prepare a master thesis according to formal rules.
2. The student has the skill of applying knowledge acquired during studies to problems connected to the topic of his master thesis.
Social competences:
1. The student is capable of finding data and analyzing it. The student can work with data. He is able to formulate a research problem and a scientific hypothesis. The student is able to prepare a master thesis.
2. The student is able to complete the acquired knowledge. He is capable of finding literature.
3. The student is capable of working individually.
KW01, KW02, KW03, KU01, KU02, KU03, KK01, KK02, KK03
Assessment criteria
In a first semester each student will be obliged to discuss selected article in scope of a planned MA thesis and in a second part of the semester prepare a presentation of preliminary results of his research.
In a second semester each student will be obliged to present final results of his / her research.
Seminar will be finished (in a third semester) after a preparation of a very good thesis.
Bibliography
Tailored to a student thesis.