Moses - Foundations of Data Science

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Module / Version:
#40917 / #2

Validity:
Seit WS 2019/20

Default display language:
English

Module title:
Foundations of Data Science

Credits:
6

Responsible person:
Albayrak, Sahin

Grading:
benotet

Type of exam:
Mündliche Prüfung

Zugehörigkeit

Faculty:
Fakultät IV

Institute:
Institut für Wirtschaftsinformatik und Quantitative Methoden

Area of expertise:
34361200 FG Agententechnologien in betrieblichen Anwendungen und der Telekommunikation (AOT)

Prüfungsausschuss:
No information

Kontakt

Office:
TEL 14

Contact person:
Fricke, Stefan

E-mail address:
dai-labor-lehre@lists.tu-berlin.de

Website:

http://www.aot.tu-berlin.de

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.

Content

- 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

Pflichtgruppe:

All Courses are mandatory.

Course Name	Type	Number	Cycle	Language	SWS	VZ
Data Science	IV		WiSe	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:

This module has no requirements.

Module completion

Grading

graded

Type of exam

Oral exam

Language

German

Duration/Extent

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:
Wintersemester.

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 literature
No recommended literature given

Assigned Degree Programs

Semester:

Zeige auch ausgelaufene Studiengänge und StuPOs

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

Studiengang / StuPO	StuPOs	Verwendungen	Erste Verwendung	Letzte Verwendung
Computer Engineering (M. Sc.)	1	30	WS 2019/20	SoSe 2024
Computer Science (Informatik) (M. Sc.)	1	40	WS 2019/20	SoSe 2024
Elektrotechnik (M. Sc.)	1	20	WS 2019/20	SoSe 2024
Information Systems Management (Wirtschaftsinformatik) (M. Sc.)	1	10	WS 2019/20	SoSe 2024
Medieninformatik (M. Sc.)	1	10	WS 2019/20	SoSe 2024
Medientechnik (M. Sc.)	1	4	WiSe 2023/24	SoSe 2024
Wirtschaftsingenieurwesen (M. Sc.)	1	22	WS 2019/20	SoSe 2024

Miscellaneous

No information

Foundations of Data Science