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Masterstudium Data Science

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Links	Ehemalige LVAs, Studienplan
VoWi-Stats	9 Pflicht-LVAs 20 Wahl-LVAs

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LVAs nach Pflichtmodulen

Kein Wert

• Capture The Flag SE (Maffei)

BDHPC/FD - Big Data and High Performance Computing - Foundations

• Data-intensive Computing VU (Knees)
• Datenbanksysteme Vertiefung VU (Pichler)

FDS/CO - Fundamentals of Data Science - Core

• Data Acquisition and Survey Methods VU (Klaus Nordhausen)
• Data Stewardship VO (Rauber)

FDS/FD - Fundamentals of Data Science - Foundations

• AKSTA Statistical Computing VU (Filzmoser)

MLS/CO - Machine Learning and Statistics - Core

• Statistische Simulation und computerintensive Methoden VU (Nordhausen)

MLS/FD - Machine Learning and Statistics - Foundations

• Advanced Methods for Regression and Classification VU (Filzmoser)

VAST/FD - Visual Analytics and Semantic Technologies - Foundations

• Informationsvisualisierung VO (Miksch)

LVAs nach Wahlmodulen

BDHPC/EX - Big Data and High Performance Computing - Extension

• Datenbanktheorie VU (Pichler)
• Effiziente Programme VU (Ertl)
• GPU Architectures and Programming VU (Bartocci)
• Heuristic Optimization Techniques VU (Raidl)
• High Performance Computing VU (Träff)

FDS/EX - Fundamentals of Data Science - Extension

• Data Stewardship UE (Rauber)
• Organizational Aspects of IT-Security VU (Weippl)
• Software Security VU (Weippl)
• User Research Methods VU (Frauenberger)

MLS/EX - Machine Learning and Statistics - Extension

• Business Intelligence VU (Tjoa)
• Problem Solving and Search in AI VU (Musliu)
• Selbstorganisierende Systeme VU (Rauber)
• Social Network Analysis VU (Neidhardt)

VAST/CO - Visual Analytics and Semantic Technologies - Core

• Advanced Information Retrieval VU (Rauber)

VAST/EX - Visual Analytics and Semantic Technologies - Extension

• Knowledge-based Systems VU (Egly, Eiter, Tompits)
• Semi-Automatic Information and Knowledge Systems VU (Sabou, Lanzenberger)
• Verarbeitung deklarativen Wissens VO (Egly)
• Visualisierung 2 VU (Gröller)

VAST/FD - Visual Analytics and Semantic Technologies - Foundations

• Einführung in Semantic Systems VU (Tjoa)
• Psychologische Grundlagen der Visualisierung VO (Pohl)

Alphabetisch

A

• AKSTA Statistical Computing VU (Filzmoser)
• Advanced Information Retrieval VU (Rauber)
• Advanced Methods for Regression and Classification VU (Filzmoser)

B

• Business Intelligence VU (Tjoa)

C

• Capture The Flag SE (Maffei)

D

• Data Acquisition and Survey Methods VU (Klaus Nordhausen)
• Data Stewardship UE (Rauber)
• Data Stewardship VO (Rauber)
• Data-intensive Computing VU (Knees)
• Datenbanksysteme Vertiefung VU (Pichler)

D (Fortsetzung)

• Datenbanktheorie VU (Pichler)

E

• Effiziente Programme VU (Ertl)
• Einführung in Semantic Systems VU (Tjoa)

G

• GPU Architectures and Programming VU (Bartocci)

H

• Heuristic Optimization Techniques VU (Raidl)
• High Performance Computing VU (Träff)

I

• Informationsvisualisierung VO (Miksch)

K

• Knowledge-based Systems VU (Egly, Eiter, Tompits)

O

• Organizational Aspects of IT-Security VU (Weippl)

P

• Problem Solving and Search in AI VU (Musliu)

P (Fortsetzung)

• Psychologische Grundlagen der Visualisierung VO (Pohl)

S

• Selbstorganisierende Systeme VU (Rauber)
• Semi-Automatic Information and Knowledge Systems VU (Sabou, Lanzenberger)
• Social Network Analysis VU (Neidhardt)
• Software Security VU (Weippl)
• Statistische Simulation und computerintensive Methoden VU (Nordhausen)

U

• User Research Methods VU (Frauenberger)

V

• Verarbeitung deklarativen Wissens VO (Egly)
• Visualisierung 2 VU (Gröller)