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Foundations of Data Science



#40917 / #2

Seit WS 2019/20

Fakultät IV

TEL 14

Institut für Wirtschaftsinformatik und Quantitative Methoden

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

Albayrak, Sahin

Fricke, Stefan

POS-Nummer PORD-Nummer Modultitel
2348269 40079 Foundations of Data Science

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 Name Type Number Cycle Language SWS
Data Science IV WS German 4

Workload and Credit Points

Data Science (IV):

Workload description Multiplier Hours Total
Attendance 15.0 4.0h 60.0h
Pre/post processing 15.0 8.0h 120.0h
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:

No information

Module completion



Type of exam

Oral exam




30 minutes

Duration of the Module

This module can be completed in one semester.

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):

Verwendungen (2)
Studiengänge: 1 Stupos: 1 Erstes Semester: SoSe 2020 Letztes Semester: SoSe 2021

This moduleversion is used in the following modulelists:


No information