Vorlesungsverzeichnis - uni-potsdam.deAnwendungen für Datenanalyse-Verfahren erstrecken sich von...

VorlesungsverzeichnisMaster of Science - Data SciencePrüfungsversion Wintersemester 2018/19

Wintersemester 2019/20

Inhaltsverzeichnis

Inhaltsverzeichnis

Abkürzungsverzeichnis 5

Bridge Modules...................................................................................................................................................... 6

FM2 - Foundations of Computer Science 6

78421 V - Grundlagen der Informatik 6

78422 U - Grundlagen der Informatik 6

MAT-DSBM1 - Foundations of Stochastics 6

78074 VU - Foundations of Stochastics 7

Compulsory Modules............................................................................................................................................ 7

MATVMD837 - Statistical Data Analysis 7

78069 VU - Statistical Data Analysis 7

MATVMD838 - Bayesian Inference and Data Assimilation 7

INF-DS-C1 - Machine Learning 7

78498 VU - Maschinelles Lernen & Intelligente Datenanalyse II 7

INF-DS-C2 - Data Infrastructures and Software Engineering 7

78434 VU - Software Engineering I 8

78438 S - Themen der sprachbasierten Sicherheit 8

78492 VU - Paralleles Rechnen II: Architekturen und Middleware 9

78516 PJ - Themen der sprachbasierten Sicherheit 9

78517 PR - Principles of Data- and Knowledge-Base Systems 9

78518 V - Principles of Data- and Knowledge-Base Systems 9

78519 U - Principles of Data- and Knowledge-Base Systems 9

78662 VU - Verteiltes Datenmanagement 10

78664 V - Big Data Systeme 10

INF-DS-C3 - Data Science and Business Analytics 10

78428 VU - Data Science 10

INF-DS-C4 - Applied Data Science 11

75862 B - Analysis of high-throughput sequencing data 11

75935 VU - Bioinformatik biologischer Sequenzen / Evolutionary Genomics 11

76281 VU - Remote Sensing of the Environment 11

78072 VU - Ringvorlesung interdisziplinäre Mathematik: Eine projektorientierte Einführung 11

78115 VU - Social Media Research 12

78451 U - Declarative Problem Solving and Optimization 13


78676 V - Methods of Cloud Computing 14

Elective Modules - Research Modules.............................................................................................................. 14

INF-DS-RMA - Research Module A 14

78448 PJ - Extensive Declarative Problem Solving 15

78468 PJ - Extensive Logistics Technology 15

78507 PJ - Research Module A 15

INF-DS-RMB - Research Module B 15

2Abkürzungen entnehmen Sie bitte Seite 5

Inhaltsverzeichnis


78464 S - Cognitive technologies 16

78512 PJ - Research Module B 16


Elective Modules - Advanced Module............................................................................................................... 16

MAT-DSAM2A - Advanced Statistical Data Analysis A 16

MAT-DSAM2B - Advanced Statistical Data Analysis B 16

75428 VS - Bayesian Linear Modeling 16

MAT-DSAM3A - Advanced Data Assimilation and Modeling A 16

MAT-DSAM3B - Advanced Data Assimilation and Modeling B 16

MAT-DSAM8A - Mathematical Foundations of Data Science A 16

78067 VU - Partielle Differentialgleichungen I 17

78068 VU - Stochastic Analysis 17

MAT-DSAM8B - Mathematical Foundations of Data Science B 17

78055 VU - Computermathematik II: Numerische Mathematik 17

78856 VU - Stochastics 18

BM3 - Advanced Problem Solving Techniques 18

78470 V - Advanced Problem Solving Techniques 18

78471 U - Advanced Problem Solving Techniques 18

78472 PJ - Advanced Problem Solving Techniques 19

78473 PR - Advanced Problem Solving Techniques 19

INF-DSAM1A - Advanced Machine Learning A 19


INF-DSAM1B - Advanced Machine Learning B 20


INF-DSAM4A - Advanced Infrastructures and Software Engineering A 20



INF-DSAM4B - Advanced Infrastructures and Software Engineering B 21

78432 FS - Software Engineering 21




INF-DSAM5A - Advanced Business Analytics A 22

INF-DSAM5B - Advanced Business Analytics B 22

78120 S - Social Media & Business Analytics 22

78122 SK - Social Media Research Project 23

78862 S - Machine Learning in BPM 24

INF-DSAM6A - Advanced Applied Data Science A 24

75525 U - Advanced Natural Language Processing 24

75526 V - Advanced Natural Language Processing 25

78122 SK - Social Media Research Project 25

INF-DSAM6B - Advanced Applied Data Science B 26

76281 VU - Remote Sensing of the Environment 26

78115 VU - Social Media Research 26


Inhaltsverzeichnis

78398 PJ - Interoperability in the IoT 28

78652 S2 - Social Media Mining 28

78654 S - Behavioral Authentication with Machine Learning 28

78862 S - Machine Learning in BPM 28

78865 VS - Data Analysis using R, 1 - Statistical Epidemiology 29

INF-DSAM7 - Computer Engineering for Big Data 29

78467 PJ - Extensive Solver Construction 29



INF-DSAM9 - Computational Foundations of Data Science 30

78410 VU - Multimedia-Technologie 30

78429 VU - Codierungstheorie 30

78451 U - Declarative Problem Solving and Optimization 32

78466 S - Current Topics in Computational Intelligence 32



INF-DSAM10 - Research Data Management, Law, and Ethics 33

INF-DSAM11 - Applied Data Science Internship 33

78448 PJ - Extensive Declarative Problem Solving 33

78467 PJ - Extensive Solver Construction 34

78468 PJ - Extensive Logistics Technology 34

Glossar 35


Abkürzungsverzeichnis

Abkürzungsverzeichnis

Veranstaltungsarten

AG Arbeitsgruppe

B Blockveranstaltung

BL Blockseminar

DF diverse Formen

EX Exkursion

FP Forschungspraktikum

FS Forschungsseminar

FU Fortgeschrittenenübung

GK Grundkurs

KL Kolloquium

KU Kurs

LK Lektürekurs

LP Lehrforschungsprojekt

OS Oberseminar

P Projektseminar

PJ Projekt

PR Praktikum

PU Praktische Übung

RE Repetitorium

RV Ringvorlesung

S Seminar

S1 Seminar/Praktikum

S2 Seminar/Projekt

S3 Schulpraktische Studien

S4 Schulpraktische Übungen

SK Seminar/Kolloquium

SU Seminar/Übung

TU Tutorium

U Übung

UN Unterricht

UP Praktikum/Übung

V Vorlesung

VP Vorlesung/Praktikum

VS Vorlesung/Seminar

VU Vorlesung/Übung

WS Workshop

Veranstaltungsrhytmen

wöch. wöchentlich

14t. 14-täglich

Einzel Einzeltermin

Block Block

BlockSa Block (inkl. Sa)

BlockSaSo Block (inkl. Sa,So)

Andere

N.N. Noch keine Angaben

n.V. Nach Vereinbarung

LP Leistungspunkte

SWS Semesterwochenstunden

Belegung über PULS

PL Prüfungsleistung

PNL Prüfungsnebenleistung

SL Studienleistung

L sonstige Leistungserfassung

5

Master of Science - Data Science - Prüfungsversion Wintersemester 2018/19

Vorlesungsverzeichnis

Bridge Modules

FM2 - Foundations of Computer Science

78421 V - Grundlagen der Informatik

Gruppe Art Tag Zeit Rhythmus Veranstaltungsort 1.Termin Lehrkraft

1 V N.N. N.N. wöch. N.N. N.N. Dr. Henning Bordihn

Kommentar

Algorithmen und Datenstrukturen: Wachstum von Funktionen und O-Notation; Divide and Conquer; Sortieren und Suchen;elementare Datenstrukturen; dynamisches Programmieren; elementare Graphalgorithmen

Formale Sprachen: Chomsky-Hierarchie; reguläre Sprachen und endliche Automaten; kontextfreie Sprachen undKellerautomaten; endliche Automaten; Turingmaschinen

Theoretische Grundlagen: Berechenbarkeit; Halteproblem; Nichtdeterminismus; Komplexitätsklassen P und NP; Rekursion;induktive Definitionen

Die Inhalte werden über geeignete Online-Video-Vorlesungen vermittelt, z.B. von Coursera, Stanford Online oder MITOpenCourseWare.

Leistungsnachweis

mündliche Prüfung 30 Minuten

Leistungen in Bezug auf das Modul

SL 556011 - Video-Vorlesung (unbenotet)

78422 U - Grundlagen der Informatik


1 U Do 16:00 - 18:00 wöch. 3.04.1.02 17.10.2019 Dr. Henning Bordihn

Kommentar

Algorithmen und Datenstrukturen: Wachstum von Funktionen und O-Notation; Divide and Conquer; Sortieren und Suchen;elementare Datenstrukturen; dynamisches Programmieren; elementare Graphalgorithmen

Formale Sprachen: Chomsky-Hierarchie; reguläre Sprachen und endliche Automaten; kontextfreie Sprachen undKellerautomaten; Turingmaschinen

Theoretische Grundlagen: Berechenbarkeit; Halteproblem; Nichtdeterminismus; Komplexitätsklassen P und NP; Rekursion;induktive Definitionen

Die Inhalte werden über geeignete Online-Video-Vorlesungen vermittelt, z.B. von Coursera, Stanford Online oder MITOpenCourseWare.

Leistungsnachweis

mündliche Prüfung 30 Minuten


PNL 556012 - Übung (unbenotet)

MAT-DSBM1 - Foundations of Stochastics


https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung&publishid=78421https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=29https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung&publishid=78422https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=29


78074 VU - Foundations of Stochastics


Alle V Fr 08:15 - 09:45 wöch. 3.06.H07 18.10.2019 Dr. Peter Keller

Alle V Mo 10:15 - 11:45 wöch. 3.06.S19 21.10.2019 Dr. Peter Keller

Alle V Mi 14:15 - 15:45 wöch. 3.06.S28 13.11.2019 Dr. Peter Keller

1 U Mo 08:15 - 09:45 wöch. 3.06.S26 21.10.2019 Dr. Peter Keller

2 U Mi 14:15 - 15:45 wöch. 3.06.S28 23.10.2019 Dr. Peter Keller

2 U Fr 08:15 - 09:45 wöch. 3.06.S16 15.11.2019 Dr. Peter Keller


PNL 551252 - Übung oder inverted classroom (unbenotet)

Compulsory Modules

MATVMD837 - Statistical Data Analysis

78069 VU - Statistical Data Analysis


1 V Mi 12:15 - 13:45 wöch. 2.28.0.104 16.10.2019 Prof. Dr. Melina Freitag

1 U Do 16:15 - 17:45 wöch. 2.10.0.26 17.10.2019 Prof. Dr. Melina Freitag

1 V Fr 08:15 - 09:45 wöch. 3.06.S27 18.10.2019 Prof. Dr. Melina Freitag


PNL 517311 - Vertiefende Vorlesung im Bereich Statistische Datenanalyse und Übung (unbenotet)

MATVMD838 - Bayesian Inference and Data Assimilation

Für dieses Modul werden aktuell keine Lehrveranstaltungen angeboten

INF-DS-C1 - Machine Learning

78498 VU - Maschinelles Lernen & Intelligente Datenanalyse II


Alle V Mo 12:00 - 14:00 wöch. 3.01.H10 14.10.2019 Prof. Dr. Tobias Scheffer

1 U Mi 10:00 - 12:00 wöch. 3.04.0.02 16.10.2019 Prof. Dr. Tobias Scheffer

2 U Do 08:00 - 10:00 wöch. 3.04.0.02 17.10.2019 Prof. Dr. Tobias Scheffer

Kommentar

Aufbauend auf der Vorlesung Intelligente Datenanalyse beschäftigt sich die Veranstaltung vertiefend mit Algorithmen, die ausDaten lernen können. Algorithmen des maschinellen Lernens gewinnen aus Daten Modelle, mit denen sich dann Vorhersagenüber das beobachtete System treffen lassen. Anwendungen für Datenanalyse-Verfahren erstrecken sich von der Vorhersagevon Kreditrisiken über die Auswertung astronomischer Daten bis zu persönlichen Musikempfehlungen. Die Veranstaltungsetzt sich aus einem Vorlesungs- und einem Projektteil zusammen. Der Vorlesungsteil vermittelt das notwendige Wissen überDatenanalyse sowie über Matlab. Im Projektteil werden anwendungsnahe Aufgaben eigenständig bearbeitet.

Voraussetzung

Intelligente Datenenalyse

Leistungsnachweis

Projektaufgabe und mündliche Prüfung


PNL 557103 - Laborübung (unbenotet)

INF-DS-C2 - Data Infrastructures and Software Engineering


https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung&publishid=78074https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=3813https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=3813https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=3813https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=3813https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=3813https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=3813https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung&publishid=78069https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=7568https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=7568https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=7568https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung&publishid=78498https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=2913https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=2913https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=2913


78434 VU - Software Engineering I


Alle V Do 14:00 - 16:00 wöch. 3.06.H05 17.10.2019 Prof. Dr.-Ing. ChristianHammer

1 U Mo 12:00 - 14:00 wöch. 3.04.0.02 14.10.2019 Prof. Dr.-Ing. ChristianHammer

2 U Mo 14:00 - 16:00 wöch. 3.04.0.02 14.10.2019 Prof. Dr.-Ing. ChristianHammer

3 U Mi 14:00 - 16:00 wöch. 3.04.0.02 16.10.2019 Prof. Dr.-Ing. ChristianHammer

4 U Mi 16:00 - 18:00 wöch. 3.04.0.02 16.10.2019 Prof. Dr.-Ing. ChristianHammer

Kommentar

**Kursbeschreibung**: Diese Veranstaltung vermittelt theoretische Grundlagen und praktische Kompetenzen der Modellierungund der Softwareentwicklung. Neben traditionellen Ansätzen wird das moderne Paradigma der modellgetriebenenSoftwareentwicklung behandelt. Bei der Modellierung werden verschiedene Beschreibungsformen für das Verhaltenund die Struktur eines Softwaresystems oder seiner Komponenten betrachtet. Ferner werden die Kernphasen desSoftware-Entwicklungsprozesses betrachtet, von der Anforderungsanalyse über den Entwurf und die Implementierungbis zum Testen. Die modellgetriebene Softwareentwicklung umfasst Methoden und Techniken, die Software weitgehendautomatisiert aus geeigneten Modellen generieren. Der in diesem Zusammenhang bedeutsamen Verifikation vonkritischen Systemeigenschaften auf Modellebene wird durch die Behandlung von Methoden des Model CheckingRechnung getragen. Die Konzepte werden anhand von Anwendungsbeispielen und Werkzeugen demonstriert und geübt.Ausgewählte Aspekte werden vertieft und in einem Projekt angewendet. Zu den Inhalten der Lehrveranstaltung gehörenunter anderem: - Kernphasen der Softwareentwicklung und Vorgehensmodelle - Anforderungsanalyse und -spezifikation -Verhaltensmodellierung/Prozessmodellierung - Qualitätssicherung auf Modellebene insbesondere durch Model Checking- Strukturmodellierung, objektorientierte Modellierung - Software-Architekturen und Design-Patterns - ObjektorientierteImplementierung von Entwürfen - Verifikation und Validierung mit dem Schwerpunkt auf Testen - Modellierungsmethodik,Metamodellierung

Voraussetzung

Erfolgreiche Teilnahme an Theoretische Informatik I (bzw. Modellierungskonzepte der Informatik), Grundlagen derProgrammierung (I) und Programmierung (bzw. Praxis der Programmierung).

Literatur

Ian Sommerville. Software Engineering, Ninth Edition. Pearson, 2011, 0-13-705346-0 Ian Sommerville, Perdita Stevens.Software Engineering: AND Using UML, Software Engineering with Objects and Components. Pearson Education,2007, 1-4058-9258-7 Helmut Balzert. Lehrbuch der Software-Technik (Band 1): Software-Entwicklung. SpektrumAkademischer Verlag Heidelberg, 1996, 3-8274-0042-2 Perdita Stevens. Using UML: Software Engineering with Objects andComponents. Pearson Education, 2005, 0-3212-6967-5 M. Hitz, G. Kappel, E. Kapsammer, W. Retschitzegger. [email protected] Modellierung mit UML 2. dpunkt.verlag, Heidelberg, 2005, 3-89864-261-5 Edmund M. Clarke Jr., OrnaGrumberg, Doron A. Peled. Model Checking. MIT Press, 2000, 978-0-262-03270-4 Mary Poppendieck, Tom Poppendieck.Lean Software Development: An Agile Toolkit. Addison-Wesley Professional, 2003, 0-3211-5078-3

Leistungsnachweis

Am Ende des Semesters werden 6 benotete Leistungspunkte vergeben, wobei die Zensur folgendermaßen als gewichtetesMittel vergeben wird: * Klausur: 70%, * Projekt: 30%. Die Klausur muss bestanden werden.

Bemerkung

Bei Bedarf wird die Stoffvermittlung in englischer Sprache durch ein angeleitetes Selbststudium unterstützt.


PNL 557111 - Vorlesung und Übung (unbenotet)

78438 S - Themen der sprachbasierten Sicherheit


1 S Di 10:00 - 12:00 wöch. 3.04.1.03 15.10.2019 Prof. Dr.-Ing. ChristianHammer

Kurzkommentar

Achtung! Die Termine werden nach Vereinbarung festgelegt. Die hier stehenden Zeiten und Räume gelten nicht mehr.




https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung&publishid=78434https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=6375https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=6375https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=6375https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=6375https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=6375https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=6375https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=6375https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=6375https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=6375https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=6375https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung&publishid=78438https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=6375https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=6375


78492 VU - Paralleles Rechnen II: Architekturen und Middleware


1 U N.N. N.N. Block N.N. N.N. Prof. Dr. Bettina Schnor

Raum und Zeit nach Absprache

1 V N.N. N.N. Block N.N. N.N. Prof. Dr. Bettina Schnor


Kommentar

Das Modul vermittelt ein vertieftes Verst"andnis f"ur Cluster Computing und die Programmierung aktuellerHochleistungsrechner.

Voraussetzung

Vorlesung Paralleles Rechnen

Leistungsnachweis

Praktische Hausarbeit mit Abschlussvortrag und schriftlicher Ausarbeitung. Benotet werden Abschlussvortrag undAusarbeitung.



78516 PJ - Themen der sprachbasierten Sicherheit


1 PJ Di 12:00 - 14:00 wöch. 3.04.1.03 15.10.2019 Prof. Dr.-Ing. ChristianHammer

Kurzkommentar




78517 PR - Principles of Data- and Knowledge-Base Systems


1 PR N.N. N.N. wöch. N.N. N.N. Prof. Dr. Torsten Schaub,Philipp Obermeier

Literatur

Principles of Database & Knowledge-Base Systems by Jeffrey D. Ullman W. H. Freeman & Co. New York, NY, USA

78518 V - Principles of Data- and Knowledge-Base Systems


1 V Di 14:00 - 16:00 wöch. 3.06.H01 15.10.2019 Prof. Dr. Torsten Schaub,Philipp Obermeier

Literatur


78519 U - Principles of Data- and Knowledge-Base Systems


1 U Mi 16:00 - 18:00 wöch. 3.06.H01 16.10.2019 Philipp Obermeier

2 U Mi 16:00 - 18:00 wöch. 3.06.H06 16.10.2019 Philipp Obermeier

Literatur





https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung&publishid=78492https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=37https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=37https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung&publishid=78516https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=6375https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=6375https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung&publishid=78517https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=39https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=6087https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung&publishid=78518https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=39https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=6087https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung&publishid=78519https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=6087https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=6087


78662 VU - Verteiltes Datenmanagement


1 VU N.N. N.N. wöch. N.N. N.N. Thorsten Papenbrock;

Kommentar

Angaben zum Lehrinhalt in der Beschreibung aufrufbar unter https://hpi.de/studium/lehrveranstaltungen.html

Voraussetzung

Voraussetzungen werden in den Lehrinhaltsbeschreibungen unter https://hpi.de/studium/lehrveranstaltungen.html benannt.

Bemerkung

Unter https://hpi.de/studium/lehrveranstaltungen.html sind folgende Angaben aufrufbar:

• Raum und Zeit• Lehrinhalt und Leistungserfassung• Teilnehmerbegrenzung



78664 V - Big Data Systeme


1 V N.N. N.N. wöch. N.N. N.N. Prof. Dr. Tilmann Rabl

Kommentar


Voraussetzung


Bemerkung





INF-DS-C3 - Data Science and Business Analytics

78428 VU - Data Science


Alle V Sa 10:00 - 14:00 14t. 3.06.H03 19.10.2019 Prof. Dr. Tobias Scheffer

1 U Mo 10:00 - 12:00 wöch. 3.04.0.02 14.10.2019 N.N.

2 U Di 08:00 - 10:00 wöch. 3.04.0.02 15.10.2019 N.N.

3 U Di 12:00 - 14:00 wöch. 3.04.0.02 15.10.2019 N.N.

4 U Mi 08:00 - 10:00 wöch. 3.04.0.02 16.10.2019 N.N.


PNL 557121 - Vorlesung und Laborübung (unbenotet)


https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung&publishid=78662https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=5438https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung&publishid=78664https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=7610https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung&publishid=78428https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=2913https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=182https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=182https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=182https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=182


INF-DS-C4 - Applied Data Science

75862 B - Analysis of high-throughput sequencing data


1 B N.N. N.N. Block N.N. N.N. Dr. Christian Kappel

Block event, 2 weeks in lecture-free period; please contact lecturer for details at the start of the semester!

Bemerkung

This is a block couse mixing lectures and hands-on work. It will take place from February 17 to 28, 9 am to 5 pm. First examsession will be on March 11, 10 to 12 am. Please contact [email protected] for any question. You may finda rough description of the course in the Bioinformatics module guide, BIO-MBIW08 ( https://www.uni-potsdam.de/fileadmin01/projects/mnfakul/Dokumente_und_%C3%9Cbersichten/Studium_und_Lehre/Module_Guide_Bioinformatics_EN.pdf ).


PNL 557132 - Übung oder Projekt (unbenotet)

75935 VU - Bioinformatik biologischer Sequenzen / Evolutionary Genomics


Alle V Di 08:15 - 09:45 wöch. 2.25.F1.01 15.10.2019 Dr. Stefanie Hartmann

1 U Mi 08:15 - 09:45 wöch. 2.25.D0.02 16.10.2019 Dr. Stefanie Hartmann

1 U Mi 08:15 - 09:45 wöch. 2.25.D0.01 16.10.2019 Dr. Stefanie Hartmann

2 U Do 08:15 - 09:45 wöch. 2.25.D0.02 17.10.2019 Dr. Stefanie Hartmann

2 U Do 08:15 - 09:45 wöch. 2.25.D0.01 17.10.2019 Dr. Stefanie Hartmann

Kommentar

Sie benoetigen einen Account fuer die Computer in den Computer-Pools. Benutzerantrag auf https://www.chem.uni-potsdam.de/groups/pools/Studierende/studierende.html

You will need an account for the computers in the computer pools. Application forms are available from the linkabove.



76281 VU - Remote Sensing of the Environment


1 V Di 12:15 - 13:45 wöch. 2.27.1.10 15.10.2019 Prof. Dr. BodoBookhagen

1 U Di 14:15 - 15:45 wöch. 2.27.1.10 15.10.2019 Prof. Dr. BodoBookhagen



78072 VU - Ringvorlesung interdisziplinäre Mathematik: Eine projektorientierte Einführung


1 V Mi 10:15 - 11:45 wöch. 2.09.0.13 16.10.2019 apl. Prof. Dr. ChristineBöckmann, Dr. NiklasHartung, Dr. rer. nat.Han Cheng Lie, Prof. Dr.Melina Freitag

1 U Do 12:15 - 13:45 wöch. 2.09.0.14 17.10.2019 apl. Prof. Dr. ChristineBöckmann, Dr. NiklasHartung, Dr. rer. nat.


https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung&publishid=75862https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=4252https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung&publishid=75935https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=1569https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=1569https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=1569https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=1569https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=1569https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung&publishid=76281https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=5639https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=5639https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=5639https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=5639https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung&publishid=78072https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=45https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=45https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=6440https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=6440https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=7419https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=7419https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=7568https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=7568https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=45https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=45https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=6440https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=6440https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=7419


Han Cheng Lie, Prof. Dr.Melina Freitag

1 V Do 14:15 - 15:45 wöch. 2.27.0.01 17.10.2019 apl. Prof. Dr. ChristineBöckmann, Dr. NiklasHartung, Dr. rer. nat.Han Cheng Lie, Prof. Dr.Melina Freitag



78115 VU - Social Media Research


1 V Mo 14:00 - 16:00 wöch. 3.06.S27 21.10.2019 Prof. Dr. HannaKrasnova, OlgaAbramova

1 U Mo 16:00 - 18:00 wöch. 3.06.S27 28.10.2019 Prof. Dr. HannaKrasnova, OlgaAbramova

Voraussetzung

Interest in research methods and Social Media. This class is limited to 50 students. The class will be held in English.

Please install R and R studio before the session on Mon 09.12. Students are assummed to complete exercises in R on theirown laptops.

Literatur

Collis J. and Hussez, R. (2009) "Business Research: A Practical Guide for Undergraduate and Postgraduate Students”.

Leistungsnachweis

In-class assignments and written exam.

Initially, the course is worth 12 ECTS. If you wish, we can award you less (6 or 9 ECTS) for regular participation.

Erasmus students will get a Course Completion Certificate (Leistungsnachweis) which they can forward to the InternationalOffice or Home University.


https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=7419https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=7568https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=7568https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=45https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=45https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=6440https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=6440https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=7419https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=7419https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=7568https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=7568https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung&publishid=78115https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=6090https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=6090https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=6730https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=6730https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=6090https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=6090https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=6730https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=6730


Lerninhalte

The first session of this course will take place on the 21.Oct at 14:15.

As the adoption and usage of social applications is on the rise (e.g. Facebook, Airbnb, Twitter, PatientsLikeMe), there is agrowing interest in understanding behavior and perceptions of users, as well as the impact of this use on businesses, publicsector and society as a whole. Against this background, the goal of this class is to empower students with a set of researchapproaches and methods that can be used to understand this phenomenon. Among others, course participants will be trainedto collect and analyze qualitative and quantitative data that reflects usage patterns and perceptions of users of various socialapplications. This course may serve as a sound methodological preparation for a master thesis or a seminar at the chair ofBusiness Informatics, esp. Social Media and Data Science.

The class will follow the following schedule

Mon 21.10 Introduction (Prof. Hanna Krasnova | Olga Abramova)

Mon 28.10 Qualitative Data Analysis Module (Prof. Hanna Krasnova)






Mon 09.12 Data Analysis using R Module (Olga Abramova) - please install R and R studio before the session!

Mon 16.12 Data Analysis using R Module (Olga Abramova)




Mon 27.01 Data Analysis using R Module | Exam Review (Prof. Hanna Krasnova | Olga Abramova)

Mon 03.02 – Exam (90 min)



78451 U - Declarative Problem Solving and Optimization


1 U Mo 16:00 - 18:00 wöch. 3.06.S23 14.10.2019 Prof. Dr. Torsten Schaub,Francois Laferriere

Kommentar

Answer Set Programming (ASP) is a prime approach to declarative problem solving. Although initially tailored to modelingproblems in the area of Knowledge Representation and Reasoning (KRR), its attractive combination of a rich yet simplemodeling language with high-performance solving capacities has sparked interests in many other areas even beyond KRR.This course presents a detailed introduction to ASP, aiming at using ASP languages and systems for solving applicationproblems. Starting from the essential formal foundations, it introduces ASP's solving technology, modeling language andmethodology, while illustrating the overall solving process by practical examples.

Literatur

Answer Set Solving in Practice by Martin Gebser, Roland Kaminski, Benjamin Kaufmann, and Torsten Schaub SynthesisLectures on Artificial Intelligence and Machine Learning, Morgan and Claypool Knowledge Representation, Reasoning, andthe Design of Intelligent Agents The Answer-Set Programming Approach by Michael Gelfond and Yulia Kahl CambridgeUniversity Press

Leistungsnachweis

Exam and assignments


https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung&publishid=78451https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=39https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=7261




78662 VU - Verteiltes Datenmanagement


1 VU N.N. N.N. wöch. N.N. N.N. Thorsten Papenbrock;

Kommentar


Voraussetzung


Bemerkung





78676 V - Methods of Cloud Computing


1 U N.N. N.N. Einzel N.N. N.N. Prof. Dr. Andreas Polze

1 V N.N. N.N. wöch. N.N. N.N. Prof. Dr. Andreas Polze

Kommentar


Voraussetzung


Bemerkung





Elective Modules - Research Modules

INF-DS-RMA - Research Module A


https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung&publishid=78662https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=5438https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfo&publishSubDir=veranstaltung&publishid=78676https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=1132https://puls.uni-potsdam.de/qisserver/rds?state=verpublish&status=init&vmfile=no&moduleCall=webInfo&publishConfFile=webInfoPerson&publishSubDir=personal&keep=y&personal.pid=1132


78448 PJ - Extensive Declarative Problem Solving


1 PJ N.N. N.N. wöch. N.N. N.N. Prof. Dr. Torsten Schaub

Kommentar

In this project, student teams build software systems whose core consists of problem solvers for combinatorial (optimization)problems.

Voraussetzung

Knowledge in ASP and/or SAT.

Leistungsnachweis

Implementation und Dokumentation

Kurzkommentar

Gemeinsame Auftaktveranstaltung für alle Projektangebote der Professur Wissensverarbeitung und Informationssysteme am26.10.17 um 18 Uhr im HS 3.06.H01!


SL 557142 - Übung oder Projekt (unbenotet)

78468 PJ - Extensive Logistics Technology


1 PJ N.N. N.N. wöch. N.N. N.N. Prof. Dr. Torsten Schaub

Kommentar

TODO - in English

Leistungsnachweis

Implementation und Dokumentation

Kurzkommentar

Gemeinsame Auftaktveranstaltung für alle Projektangebote der Professur Wissensverarbeitung und Informationssysteme am26.10.17 um 18 Uhr im HS 3.06.H01!



78507 PJ - Research Module A


1 PJ N.N. N.N. Block N.N. N.N. Prof. Dr. Tobias Scheffer



SL 557141 - Vorlesung oder Seminar (unbenotet)


INF-DS-RMB - Research Module B




Kurzkommentar





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78464 S - Cognitive technologies


1 S Di 12:00 - 14:00 wöch. 3.04.1.02 15.10.2019 Prof. Dr. Torsten Schaub,Javier Romero Davila

1 S Di 12:00 - 14:00 Einzel 3.06.S16 22.10.2019 Prof. Dr. Torsten Schaub,Javier Romero Davila

1 S Di 12:00 - 14:00 Einzel 3.06.S27 19.11.2019 Prof. Dr. Torsten Schaub,Javier Romero Davila



78512 PJ - Research Module B


1 PJ N.N. N.N. Block N.N. N.N. Prof. Dr. Tobias Scheffer




78516 PJ - Themen der sprachbasierten Sicherheit


1 PJ Di 12:00 - 14:00 wöch. 3.04.1.03 15.10.2019 Prof. Dr.-Ing. ChristianHammer

Kurzkommentar




Elective Modules - Advanced Module

MAT-DSAM2A - Advanced Statistical Data Analysis A


MAT-DSAM2B - Advanced Statistical Data Analysis B

75428 VS - Bayesian Linear Modeling


1 VS Do 14:00 - 16:00 wöch. 2.14.0.09 17.10.2019 Dr. phil. Raban Titus vonder Malsburg

MAT-DSAM3A - Advanced Data Assimilation and Modeling A


MAT-DSAM3B - Advanced Data Assimilation and Modeling B


MAT-DSAM8A - Mathematical Foundations of Data Science A


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78067 VU - Partielle Differentialgleichungen I


1 V Mo 10:15 - 11:45 wöch. 2.09.1.10 14.10.2019 Prof. Dr. Markus Klein

1 U Mo 14:15 - 15:45 wöch. 2.09.0.12 14.10.2019 Prof. Dr. Markus Klein

1 V Do 16:15 - 17:45 wöch. 2.09.0.14 17.10.2019 Prof. Dr. Markus Klein



78068 VU - Stochastic Analysis


1 V Di 14:15 - 15:45 wöch. 2.09.1.10 15.10.2019 Prof. Dr. Sylvie Roelly

1 V Mi 08:15 - 09:45 wöch. 2.09.1.10 16.10.2019 Prof. Dr. Sylvie Roelly

1 U Do 08:15 - 09:45 wöch. 2.09.1.10 17.10.2019 Dr. Sara Mazzonetto

Links:

Dozentin http://www.math.uni-potsdam.de/professuren/wahrscheinlichkeitstheorie/personen/prof-dr-sylvie-roelly/

Literatur

- Durett, R. : Essentials of stochastic processes , 1999- Klenke, A. : Probability Theory, A Comprehensive Course , 2. Auflage Springer 2014- Mörters, P. and Peres, Y. : Brownian motion , Cambridge Univ. Press 2010

Leistungsnachweis

Oral or written exam

Lerninhalte

This course provides a general detailed introduction into the stochastic integration theory with respect to the Brownianmotion and the field of stochastic differential equations. The concepts taught are highly relevant for many areas of statistics,(numerical) analysis as well as financial and insurance mathematics. Stochastic analysis is also the basis for many models inthe natural and social sciences or engineering.

Zielgruppe

Master of Mathematics, Master in Data Science, Master in Physics



MAT-DSAM8B - Mathematical Foundations of Data Science B

78055 VU - Computermathematik II: Numerische Mathematik


Alle V Di 10:15 - 11:45 wöch. 2.14.0.47 15.10.2019 Dr. Wolfgang Schöbel

1 U Mi 14:15 - 15:45 wöch. 2.09.0.12 16.10.2019 Christopher Purand

2 U Di 16:15 - 17:45 wöch. 2.09.0.12 15.10.2019 Christopher Purand




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78856 VU - Stochastics


1 VU N.N. N.N. wöch. N.N. N.N. Dr. Peter Keller

Dr. Keller, Mo 10:15-11:45 R 3.06.S19

1 U N.N. N.N. wöch. N.N. N.N. N.N.

Dr. Keller, Mi 14:15-15:45 R 3.06.S28

1 U N.N. N.N. wöch. N.N. N.N. N.N.

Dr. Keller, Mo 08:15-09:45 R 3.06.S26

1 V N.N. N.N. wöch. N.N. N.N. N.N.

Dr. Keller, Fr 08:15-09:45 R 3.06.H07



BM3 - Advanced Problem Solving Techniques

78470 V - Advanced Problem Solving Techniques


1 V Fr 12:00 - 16:00 wöch. 3.06.H01 18.10.2019 Prof. Dr. Torsten Schaub,Francois Laferriere

1 V Fr 12:00 - 16:00 Einzel 3.06.H08 08.11.2019 Prof. Dr. Torsten Schaub,Javier Romero Davila

Kommentar


Literatur


Leistungsnachweis

Exam, assignments, report and talk.

Kurzkommentar

Die Vorlesung findet nur bis Dezember 2019 freitags von 12-16 Uhr im HS 03.06.H01 statt.


SL 555911 - Vorlesung (unbenotet)

78471 U - Advanced Problem Solving Techniques


1 U Mo 16:00 - 18:00 wöch. 3.06.S23 14.10.2019 Prof. Dr. Torsten Schaub,Francois Laferriere

Kommentar



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Literatur


Leistungsnachweis



SL 555912 - Übung (unbenotet)

78472 PJ - Advanced Problem Solving Techniques


1 PJ N.N. N.N. wöch. N.N. N.N. Francois Laferriere

Kommentar


Literatur


Leistungsnachweis



PNL 555914 - Projekt (unbenotet)

78473 PR - Advanced Problem Solving Techniques


1 PR N.N. N.N. wöch. N.N. N.N. Francois Laferriere

Kommentar


Literatur


Leistungsnachweis



PNL 555913 - Praktikum (unbenotet)

INF-DSAM1A - Advanced Machine Learning A







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Kommentar


Voraussetzung


Leistungsnachweis



PNL 557161 - Vorlesung und Laborübung (unbenotet)

INF-DSAM1B - Advanced Machine Learning B






Kommentar


Voraussetzung


Leistungsnachweis



PNL 557172 - Seminar (unbenotet)

INF-DSAM4A - Advanced Infrastructures and Software Engineering A







Kommentar


Voraussetzung


Leistungsnachweis



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78664 V - Big Data Systeme


1 V N.N. N.N. wöch. N.N. N.N. Prof. Dr. Tilmann Rabl

Kommentar


Voraussetzung


Bemerkung





INF-DSAM4B - Advanced Infrastructures and Software Engineering B

78432 FS - Software Engineering


1 FS Do 10:00 - 12:00 wöch. 3.04.1.02 17.10.2019 Prof. Dr.-Ing. ChristianHammer






Kurzkommentar










Kommentar


Voraussetzung



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Leistungsnachweis



PNL 557192 - Übung oder Projekt (

Vorlesungsverzeichnis - uni-potsdam.deAnwendungen für Datenanalyse-Verfahren erstrecken sich von...

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