Data Science Practical

2018-2019

Course Objective

The student learns how to translate their econometric, data science and
numerical skills in solving real-life data problems and developing
practical solutions by working in a team. Given the limited number of
weeks available for the work on this practical case, students also learn
how to work efficiently, in an organised way and under time-pressure.

Course Content

This course is a Case Study for which a group of 3-4 students are
working together on a practical case that is developed by a company or
organisation. The background and relevance are communicated by the
external coordinator (from the company or organisation). The actual data
is provided, further guidance is offered and deliverables are clearly
formulated. The group of students need to carry out the work in period 3
which consists of four weeks. A supporting team is available for
technical questions and general support. In the last week the findings
and the deliverables need to be presented by means of a public
presentation and a report of maximum 12 pages.

Teaching Methods

It is a Case Study so students need work in groups but also
independently. In the first week there are one or two opening lectures
and a meeting with the external coordinator. In the last week, the
public presentation of the report and the delivery of the report take
place.

Method of Assessment

Presentation of report (12 minutes) and the report itself (12 pages).
Teachers and external coordinators will attend presentation, read the
reports and then decide on the grade. Awards will be given the best
groups.

General Information

Course Code E_EOR2_DSPL
Credits 6 EC
Period P3
Course Level 200
Language of Tuition English
Faculty School of Business and Economics
Course Coordinator prof. dr. S.J. Koopman
Examiner prof. dr. S.J. Koopman
Teaching Staff

Practical Information

You need to register for this course yourself

Last-minute registration is available for this course.

Teaching Methods Lecture, Study Group
Target audiences

This course is also available as: