Moses - Data Science Project

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Module / Version:
#40693 / #5

Validity:
Seit SoSe 2021

Default display language:
English

Module title:
Data Science Project

Credits:
9

Responsible person:
Albayrak, Sahin

Grading:
benotet

Type of exam:
Portfolioprüfung

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:
Lommatzsch, Andreas

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

Website:

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

Learning Outcomes

Graduates of the module have gained practical experience in dealing with complex data science problems. They are able to formulate scientific questions and systematically validate them using empirical evaluations on datasets. Graduates can formulate and present the results of the examination according to scientific standards. They are able to pursue independent research approaches and to criticize foreign scientific texts.

Content

In this course, a data science problem from a scientific or industrial domain is treated in a practice-oriented manner. The aim of the project is to formulate and validate a scientific question. For this purpose, own approaches to solving the problem are developed and implemented. The approach and the results of the validation are documented in a scientific report and presented in a presentation. Students deal in particular with the following topics: - Machine Learning - Feature Extraction - Deep Learning - Data Preprocessing - Model Evaluation - Machine Learning Libraries - Scientific Writing

Module Components

Pflichtteil:

All Courses are mandatory.

Course Name	Type	Number	Cycle	Language	SWS	VZ
Data Science Project	PJ	0435 L 773	SoSe	English	4

Workload and Credit Points

Data Science Project (PJ):

Workload description	Multiplier	Hours	Total
Appointments / presence	15.0	6.0h	90.0h
Design, implementation, evaluation	15.0	6.0h	90.0h
Preparation & follow-up work	15.0	6.0h	90.0h
			270.0h(~9 LP)

The Workload of the module sums up to 270.0 Hours. Therefore the module contains 9 Credits.

Description of Teaching and Learning Methods

Project work in groups, milestone planning, presentations, report.

Requirements for participation and examination

Desirable prerequisites for participation in the courses:

Basic data science knowledge

Mandatory requirements for the module test application:

This module has no requirements.

Module completion

Grading

graded

Type of exam

Portfolio examination

Type of portfolio examination

100 Punkte insgesamt

Language

English

Test elements

Name	Points	Categorie	Duration/Extent
(Deliverable assessment) Milestone presentations	20	oral	3 x 20 minutes
(Deliverable assessment) Project report	30	written	> 10 pages
(Deliverable assessment) Project results	50	practical	13 weeks

Grading scale

Notenschlüssel »Notenschlüssel 2: Fak IV (2)«

Gesamtpunktzahl	1.0	1.3	1.7	2.0	2.3	2.7	3.0	3.3	3.7	4.0
100.0pt	95.0pt	90.0pt	85.0pt	80.0pt	75.0pt	70.0pt	65.0pt	60.0pt	55.0pt	50.0pt

Test description (Module completion)

No information

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:
Sommersemester.

Maximum Number of Participants

The maximum capacity of students is 20.

Registration Procedures

Qispos/SAP/examination office. Additionally, a registration on the ISIS course page is mandatory.

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	20	SoSe 2021	SoSe 2024
Computer Science (Informatik) (M. Sc.)	1	27	SoSe 2021	SoSe 2024
Elektrotechnik (M. Sc.)	1	17	SoSe 2021	SoSe 2024
Information Systems Management (Wirtschaftsinformatik) (M. Sc.)	2	15	SoSe 2021	SoSe 2024
Wirtschaftsingenieurwesen (M. Sc.)	1	7	SoSe 2021	SoSe 2024

Miscellaneous