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Seit WS 2019/20


Foundations of Data Science


Albayrak, Sahin


Mündliche Prüfung


Fakultät IV

Institut für Wirtschaftsinformatik und Quantitative Methoden

34361200 FG Agententechnologien in betrieblichen Anwendungen und der Telekommunikation (AOT)

No information


TEL 14

Fricke, Stefan


Learning Outcomes

This course gives a fundamental introduction to supervised Machine Learning which is being used in the Data Science domain. Graduates of the module are able to apply supervised learning methods to new problems. In doing so, they are familiar with fundamental properties - in particular assumptions, limitations and statistical derivations - of the treated methods.


- Linear Regression - Empirical Risk Minimization - Model Assessment and Model Selection - Bias-Variance Decomposition - Bayesian Decision Theory - Naïve Bayes Classifier - Linear Classifiers - Neural Networks

Module Components


All Courses are mandatory.

Course NameTypeNumberCycleLanguageSWSVZ
Data ScienceIVWiSeGerman4

Workload and Credit Points

Data Science (IV):

Workload descriptionMultiplierHoursTotal
Pre/post processing15.08.0h120.0h
180.0h(~6 LP)
The Workload of the module sums up to 180.0 Hours. Therefore the module contains 6 Credits.

Description of Teaching and Learning Methods

Lecture with exercises

Requirements for participation and examination

Desirable prerequisites for participation in the courses:

Programming experience in Python or any other object-oriented programming language.

Mandatory requirements for the module test application:

This module has no requirements.

Module completion



Type of exam

Oral exam




30 minutes

Duration of the Module

The following number of semesters is estimated for taking and completing the module:
1 Semester.

This module may be commenced in the following semesters:

Maximum Number of Participants

The maximum capacity of students is 20.

Registration Procedures

The registration can be done via QISPOS or in the Prüfungsamt. In addition we require registration on the respective ISIS course page.

Recommended reading, Lecture notes

Lecture notes

Availability:  unavailable


Electronical lecture notes

Availability:  unavailable



Recommended literature
No recommended literature given

Assigned Degree Programs

This module is used in the following Degree Programs (new System):

Studiengang / StuPOStuPOsVerwendungenErste VerwendungLetzte Verwendung
Computer Engineering (M. Sc.)130WS 2019/20SoSe 2024
Computer Science (Informatik) (M. Sc.)140WS 2019/20SoSe 2024
Elektrotechnik (M. Sc.)120WS 2019/20SoSe 2024
Information Systems Management (Wirtschaftsinformatik) (M. Sc.)110WS 2019/20SoSe 2024
Medieninformatik (M. Sc.)110WS 2019/20SoSe 2024
Medientechnik (M. Sc.)14WiSe 2023/24SoSe 2024
Wirtschaftsingenieurwesen (M. Sc.)122WS 2019/20SoSe 2024


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