Moses - Algorithmics for Discrete Data Science

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Diese Modulbeschreibung gilt nicht im aktuellen Semester.

Die Modulbeschreibung gilt nur für den Zeitraum WS 2018/19 - WiSe 2021/22. Die Version für das aktuelle Semester (SoSe 2024) finden Sie hier: Modulbeschreibung des SoSe 2024

Module / Version:
#40913 / #1

Validity:
WS 2018/19 - WiSe 2021/22

Default display language:
English

Module title:
Algorithmics for Discrete Data Science

Credits:
6

Responsible person:
Niedermeier, Rolf

Grading:
benotet

Type of exam:
Schriftliche Prüfung

Zugehörigkeit

Faculty:
Fakultät IV

Institute:
Institut für Softwaretechnik und Theoretische Informatik

Area of expertise:
34351100 FG Algorithmik und Komplexitätstheorie

Prüfungsausschuss:
No information

Kontakt

Office:
TEL 5-1

Contact person:
Thielcke, Christlinde

E-mail address:
lehre@akt.tu-berlin.de

Website:

http://www.akt.tu-berlin.de/menue/teaching/

Learning Outcomes

Students who have completed this module can design and analyze algorithms for combinatorial data science problems. When facing a concrete computational problem, they are able to choose a strategy to efficiently solve the problem within provable performance guarantees. This includes strategies for solving problems that are computationally hard in the worst case. In particular, the students know about algorithmic research topics in discrete data science.

Content

Algorithm design and analysis for the classical computation model as well as alternative models of computation. The various models (including RAM, memory hierarchy, online, streaming, etc.) are employed in several fundamental problem domains. These domains include: - Network analysis, - Sequence analysis, and - Matrix analysis.

Module Components

Pflichtgruppe:

All Courses are mandatory.

Course Name	Type	Number	Cycle	Language	SWS	VZ
Algorithmics for Discrete Data Science	IV	0434 L 239	k.A.	English	4

Workload and Credit Points

Algorithmics for Discrete 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

The course consists of roughly 3/4 lecture and 1/4 tutorial parts; in the tutorials concrete problems are solved together.

Requirements for participation and examination

Desirable prerequisites for participation in the courses:

a) obligatory: basic knowledge on algorithm design b) desirable: basic understanding of approximation and parameterized algorithmics; participation in the course Advanced Algorithmics

Mandatory requirements for the module test application:

This module has no requirements.

Module completion

Grading

graded

Type of exam

Written exam

Language

English

Duration/Extent

90 min

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:
Winter- und Sommersemester.

Maximum Number of Participants

This module is not limited to a number of students.

Registration Procedures

Please register at QISPOS or directly at the Examination Office.

Recommended literature
Current research literature related to the course will be made available.

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
This module is not used in any degree program.

Students of other degrees can participate in this module without capacity testing.

Miscellaneous

This course is not offered regularly, you will find detailed information on our website: http://www.akt.tu-berlin.de/menue/teaching/

Algorithmics for Discrete Data Science