Syllabus
Registration via LPIS
Day | Date | Time | Room |
---|---|---|---|
Tuesday | 09/05/17 | 01:00 PM - 04:00 PM | TC.0.01 ERSTE |
Wednesday | 09/06/17 | 01:00 PM - 04:00 PM | TC.0.01 ERSTE |
Monday | 09/11/17 | 08:00 AM - 11:00 AM | D5.0.001 |
In these 2 3hrs Tutorials and entry exam, the students will repeat the prerequisites learnt in previous courses such as
- BIS 1
- Introduction to Statistics (CBK)
necessary to qualify for the SBWL "Data Science". You will also discuss and learn about more general skills necessary for a "Data Scientist", such as analytical, logical thinking and problem solving.
This entry course for the SBWL "Data Science" consists of two (attendance optional) tutorial blocks á 3hrs and concludes with an (obligatory) 90min written entry exam that will be held on 11. Sept. 2017.
The exam will consist of 3 blocks:
- Betriebliche Informationssysteme
- Statistics
- Analytical Thinking
Each block will consist of both multiple choice and open questions.
Passing the exam is obligatory to enter the SBWL "Data Science".
"Greencard":
Students who achieved a grade of "Sehr Gut (1)" in two out of the following courses
"Grundzüge der Programmierung" + "Datenbanksysteme" + "Einführung in die Statistik"
are automatically qualified for the SBWL, but should nevertheless complete the entry exam, since it will serve as the first partial assessment for the SBWL course "Data Processing 1".
ATTENTION: Students who want to make use of this "Greencard-Option" should send a confirmation (Sammelzeugnis) of the nessesary grades in advance to backoffice@ai.wu.ac.at with the subjectline "Greencard SBWL Data Science".
It is recommended to have passed positively the courses
- Betriebliche Informationssysteme (BIS 1) and
- Statistics
from the Common Body of Knowledge (CBK) of the Bachelor Programme of BusinessEconomics and Social Sciences.
Particular parts (mostly, chapters 3, 8, 9, 10) of the Book “Wirtschaftsinformatik”, 11th edition by Hans Robert Hansen / Jan Mendling / Gustaf Neumann
as well as from the course material of "Statistics" (all chapters) will be repeated in the tutorials.
Additionallty, we recommend skills such as analytical thinking requires from a Data Scientist, which we will train with for instance typical "interview questions" from Data Science companies. Some examples will be presented in the tutorials.
Back