Kies de Nederlandse taal
Course module: 880022-M-6
Data Mining for Business and Governance
Course info
Course module880022-M-6
Credits (ECTS)6
CategoryMA (Master)
Course typeCourse
Language of instructionEnglish
Offered byTilburg University; Tilburg School of Humanities and Digital Sciences; TSH: Department Cognitive Science and AI; TSHD: Department Cognitive Science and AI;
Is part of
M Communication and Information Sciences
M Data Science and Society
dr. M. Atzmüller
Other course modules lecturer
Ç. Güven
Other course modules lecturer
prof. dr. E.O. Postma
Other course modules lecturer
Academic year2019
Starting block
Course mode
Registration openfrom 20/08/2019 up to and including 18/10/2019
After the course the student will be able to:

1.         Indicate important components and tools in the data science ecosystem.

2.         Describe and explain the elementary principles of data mining and their application in different contexts and domains.

3.         Apply standard data preprocessing and data mining algorithms.

4.         Analyze and evaluate elementary data mining experiments.

5.         Draw conclusions on the potential and limitations of data, algorithms, and models, and their application in multidisciplinary contexts (e.g. teams, bridging between programmers and strategic management).


Data Mining for Business and Governance will be accessible for all students (no technical background required). During the course, students will complete mandatory assignments in which they will train their basic data mining skills in the domain of social media and behaviour. The experiments and assignments will be performed with open-source data mining software (jupyter, pandas, and scikit-learn). There will be one midterm exam to ensure that students keep on track with the course contents. The course is completed with a written exam.
Data Science methods are becoming the main tools for acquiring information both in business context and in scientific research. The course offers a thorough introduction in the use of data mining for analysis of various domains. Upon completion of the course, students will have acquired the skills necessary to apply data mining to extract information from large data sets and transform it into an understandable structure. In addition, students will be familiarized with advanced topics, including deep learning, time series and graph analyses. The perspective of the course is application-oriented and serves to provide students with the knowledge and experience that is in line with the current demand for skilled data scientists. 

Compulsory Reading
  1. Research papers, see Blackboard.
“Due to limited capacity, this course is currently not open for external students.”
Contact person
prof. dr. E.O. Postma
Timetable information
Data Mining for Business and Governance
Written test opportunities
Written test opportunities (HIST)
Midterm (20%) / Midterm (20%)MIDTERM_01BLOK 1119-09-2019
Schriftelijk (80% / Written (80%EXAM_01BLOK 1116-10-2019
Schriftelijk (80% / Written (80%EXAM_01BLOK 1209-01-2020
Midterm (20%) / Midterm (20%)MIDTERM_01BLOK 1209-01-2020
Midterm (20%) / Midterm (20%)MIDTERM_01BLOK 3120-02-2020
Midterm (20%) / Midterm (20%)MIDTERM_01BLOK 3209-03-2020
Schriftelijk (80% / Written (80%EXAM_01BLOK 3126-05-2020
Schriftelijk (80% / Written (80%EXAM_01BLOK 3216-06-2020
Required materials
Recommended materials
Written (80%

Final Result

Midterm (20%)

Kies de Nederlandse taal