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Course module: 880022-M-6
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; TSH: Department Cognitive Science and AI;
Is part of
M Communication and Information Sciences
M Data Science and Society
Lecturer(s)
Lecturer
C.D. Emmery, MSc
Other course modules lecturer
Lecturer
Ç. Güven
Other course modules lecturer
Lecturer
G.R. Nápoles
Other course modules lecturer
Academic year2020
Starting block
BLOK 1/  BLOK 3
Course mode
Full-time
RemarksCaution: this information is subject to change
Registration openfrom 20/08/2020 up to and including 20/08/2021
Aims
Aims
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.         Employ several preprocessing and data representation techniques, and supervised and unsupervised learning algorithms.
4.         Analyze and evaluate reproducible data mining experiments.
5.         Draw conclusions on the potential and limitations of data, algorithms, and models, and their application in society.
 
Specifics
Data Mining for Business and Governance will be accessible for all students (no technical background required). During the course, students will complete  assignments in which they will train their basic data mining skills, gain insights from data, and conduct reproducible research. The assignments will be performed with open-source 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.
Content
 
Steadily increasing computing power, data sources, and connectivity have made data science an important component in both industry and parts of scientific research. This course offers an introduction to this intersection of statistics, computer science, and machine learning in various domains. Upon completion of the course, students will have acquired the skills necessary to  analyze, and interpret data. Additionally, students will be familiarized with a range of algorithms for automated decision making, and methods of critically evaluating their performance and impact on society. 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, and computational researchers.
 
Compulsory Reading
Research papers, see Canvas 


“Due to limited capacity, this course is currently not open for external students.”
Course available for exchange students
Master level, conditions apply
Course available for exchange students
Master level, conditions apply
Contact person
C.D. Emmery MSc
Timetable information
Data Mining for Business and Governance
Written test opportunities
DescriptionTestBlockOpportunityDate
Written test opportunities (HIST)
DescriptionTestBlockOpportunityDate
Tussentoets / MidtermMIDTERM_01BLOK 1118-09-2020
Tentamen / ExamEXAM_01BLOK 1122-10-2020
Tussentoets / MidtermMIDTERM_01BLOK 1206-01-2021
Tentamen / ExamEXAM_01BLOK 1213-01-2021
Required materials
-
Recommended materials
-
Tests
Exam

Final Result

Midterm

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