Teaching

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Courses offered by the department cover a broad spectrum of topics on capturing, managing and analysing huge datasets. In the following, we list the courses currently offered. More information regarding the content of the courses is available in the module handbook.

Current Courses of the Department (as listed in Campus)

Advanced Information Management

Exercise
2 Sh
SS 25

Number:	021152000
Lecturers:	apl. Prof. Dr. Holger Schwarz Dennis Treder-Tschechlov
Type:	Exercise
Semester hours:	2
Teaching Language:	English
Semester:	SS 25
Organisation:	Datenbanken und Informationssysteme
Content:	Siehe Vorlesung
Link:	C@MPUS

Advanced Information Management

Lecture
2 Sh
SS 25

Number:	021151000
Lecturers:	apl. Prof. Dr. Holger Schwarz
Type:	Lecture
Semester hours:	2
Teaching Language:	English
Semester:	SS 25
Organisation:	Datenbanken und Informationssysteme
Content:	Among the topics to be discussed in this course are: - XML and database technology (XML modeling, XML storage, XML query languages, XML processing) - NoSQL data management (Key value stores, MapReduce, triple stores, document stores, graph stores) - Content management (Enterprise content management, information retrieval, search technologies)
Link:	C@MPUS

Advanced Information Management

Exercise
2 Sh
SS 25

Number:	021152000
Lecturers:	apl. Prof. Dr. Holger Schwarz Dennis Treder-Tschechlov
Type:	Exercise
Semester hours:	2
Teaching Language:	English
Semester:	SS 25
Organisation:	Datenbanken und Informationssysteme
Content:	Siehe Vorlesung
Link:	C@MPUS

Advanced Information Management

Lecture
2 Sh
SS 25

Number:	021151000
Lecturers:	apl. Prof. Dr. Holger Schwarz
Type:	Lecture
Semester hours:	2
Teaching Language:	English
Semester:	SS 25
Organisation:	Datenbanken und Informationssysteme
Content:	Among the topics to be discussed in this course are: - XML and database technology (XML modeling, XML storage, XML query languages, XML processing) - NoSQL data management (Key value stores, MapReduce, triple stores, document stores, graph stores) - Content management (Enterprise content management, information retrieval, search technologies)
Link:	C@MPUS

Data Science mit Python

Exercise
3 Sh
SS 25

Number:	021100105
Lecturers:	Dr. rer. nat. Christoph Stach
Type:	Exercise
Semester hours:	3
Teaching Language:	German
Semester:	SS 25
Organisation:	Datenbanken und Informationssysteme
Content:	Siehe Vorlesung
Link:	C@MPUS

Data Science mit Python

Lecture
1 Sh
SS 25

Number:	021100100
Lecturers:	Dr. rer. nat. Christoph Stach
Type:	Lecture
Semester hours:	1
Teaching Language:	German
Semester:	SS 25
Organisation:	Datenbanken und Informationssysteme
Content:	See German page
Link:	C@MPUS

Data Science mit Python

Exercise
3 Sh
SS 25

Number:	021100105
Lecturers:	Dr. rer. nat. Christoph Stach
Type:	Exercise
Semester hours:	3
Teaching Language:	German
Semester:	SS 25
Organisation:	Datenbanken und Informationssysteme
Content:	Siehe Vorlesung
Link:	C@MPUS

Data Science mit Python

Lecture
1 Sh
SS 25

Number:	021100100
Lecturers:	Dr. rer. nat. Christoph Stach
Type:	Lecture
Semester hours:	1
Teaching Language:	German
Semester:	SS 25
Organisation:	Datenbanken und Informationssysteme
Content:	See German page
Link:	C@MPUS

GSaME-Kolloquium

Colloquium
2 Sh
SS 25

Number:	021198100
Lecturers:	Univ.-Prof. Dr.-Ing. Bernhard Mitschang
Type:	Colloquium
Semester hours:	2
Teaching Language:	German/English
Semester:	SS 25
Organisation:	Datenbanken und Informationssysteme
Content:	nur für Mitarbeiterinnen und Doktorandinnen
Link:	C@MPUS

GSaME-Kolloquium

Colloquium
2 Sh
SS 25

Number:	021198100
Lecturers:	Univ.-Prof. Dr.-Ing. Bernhard Mitschang
Type:	Colloquium
Semester hours:	2
Teaching Language:	German/English
Semester:	SS 25
Organisation:	Datenbanken und Informationssysteme
Content:	nur für Mitarbeiterinnen und Doktorandinnen
Link:	C@MPUS

Industrial Analytics

Lecture
1 Sh
SS 25

Number:	021100300
Lecturers:	Christoph Gröger
Type:	Lecture
Semester hours:	1
Teaching Language:	German
Semester:	SS 25
Organisation:	Datenbanken und Informationssysteme
Content:	In der Veranstaltung werden insbesondere folgende Themen bearbeitet: - Einführung Industrie 4.0 und Industrial Analytics inkl. konkreten Anwendungsbeispielen aus der industriellen Praxis - Grundlagen industrieller Wertschöpfung, speziell industrielle Prozesse und Produktlebenszyklus - Industrielle IT-Systeme und industrielle Daten, z.B. MES, PLM- und ERP-Systeme - Datenplattformen für Industrial Analytics, insbesondere Data Lakes und Datenkataloge mit zugehörigen Architekturen und Technologien - Data-Analytics-Anwendungen, von Reporting bis Machine Learning - Data Governance und Datenstrategien im industriellen Umfeld - Praktische Übungen zu den o.g. Themenbereichen
Link:	C@MPUS

Industrial Analytics

Lecture
1 Sh
SS 25

Number:	021100300
Lecturers:	Christoph Gröger
Type:	Lecture
Semester hours:	1
Teaching Language:	German
Semester:	SS 25
Organisation:	Datenbanken und Informationssysteme
Content:	In der Veranstaltung werden insbesondere folgende Themen bearbeitet: - Einführung Industrie 4.0 und Industrial Analytics inkl. konkreten Anwendungsbeispielen aus der industriellen Praxis - Grundlagen industrieller Wertschöpfung, speziell industrielle Prozesse und Produktlebenszyklus - Industrielle IT-Systeme und industrielle Daten, z.B. MES, PLM- und ERP-Systeme - Datenplattformen für Industrial Analytics, insbesondere Data Lakes und Datenkataloge mit zugehörigen Architekturen und Technologien - Data-Analytics-Anwendungen, von Reporting bis Machine Learning - Data Governance und Datenstrategien im industriellen Umfeld - Praktische Übungen zu den o.g. Themenbereichen
Link:	C@MPUS

Industrial Analytics

Exercise
1 Sh
SS 25

Number:	021100305
Lecturers:	Christoph Gröger
Type:	Exercise
Semester hours:	1
Teaching Language:	German
Semester:	SS 25
Organisation:	Datenbanken und Informationssysteme
Content:	Siehe Vorlesung
Link:	C@MPUS

Industrial Analytics

Exercise
1 Sh
SS 25

Number:	021100305
Lecturers:	Christoph Gröger
Type:	Exercise
Semester hours:	1
Teaching Language:	German
Semester:	SS 25
Organisation:	Datenbanken und Informationssysteme
Content:	Siehe Vorlesung
Link:	C@MPUS

Kolloquium Datenbanksysteme

Colloquium
2 Sh
SS 25

Number:	021198000
Lecturers:	Univ.-Prof. Dr.-Ing. Bernhard Mitschang
Type:	Colloquium
Semester hours:	2
Teaching Language:	German/English
Semester:	SS 25
Organisation:	Datenbanken und Informationssysteme
Content:	for staff members and PhD students only
Link:	C@MPUS

Kolloquium Datenbanksysteme

Colloquium
2 Sh
SS 25

Number:	021198000
Lecturers:	Univ.-Prof. Dr.-Ing. Bernhard Mitschang
Type:	Colloquium
Semester hours:	2
Teaching Language:	German/English
Semester:	SS 25
Organisation:	Datenbanken und Informationssysteme
Content:	for staff members and PhD students only
Link:	C@MPUS

Modellierung

Lecture
2 Sh
SS 25

Number:	021101000
Lecturers:	Univ.-Prof. Dr.-Ing. Bernhard Mitschang apl. Prof. Dr. Holger Schwarz
Type:	Lecture
Semester hours:	2
Teaching Language:	German
Semester:	SS 25
Organisation:	Datenbanken und Informationssysteme
Content:	See German page
Link:	C@MPUS

Modellierung

Exercise
2 Sh
SS 25

Number:	021102000
Lecturers:	apl. Prof. Dr. Holger Schwarz
Type:	Exercise
Semester hours:	2
Teaching Language:	German
Semester:	SS 25
Organisation:	Datenbanken und Informationssysteme
Content:	Die Vorlesung vermittelt wie wesentliche Artefakte eines IT Systems modelliert werden, den Zusammenhang und das Zusammenspiel solcher Artefakte sowie die Rolle von Metamodellen und deren Erstellung. Die Vorlesung beinhaltet folgende Themen: - Entity-Relationship Modell und komplexe Objekte - Relationenmodell und Relationenalgebra , Überblick SQL - Transformationen von ER nach Relationen, Normalisierung - XML, DTD, XML-Schema, Info-Set, Namensräume - Metamodelle und Repository - RDF, RDF-S und Ontologien - UML - Petri Netze, Workflownetze - BPMN
Link:	C@MPUS

Modellierung

Exercise
2 Sh
SS 25

Number:	021102000
Lecturers:	apl. Prof. Dr. Holger Schwarz
Type:	Exercise
Semester hours:	2
Teaching Language:	German
Semester:	SS 25
Organisation:	Datenbanken und Informationssysteme
Content:	Die Vorlesung vermittelt wie wesentliche Artefakte eines IT Systems modelliert werden, den Zusammenhang und das Zusammenspiel solcher Artefakte sowie die Rolle von Metamodellen und deren Erstellung. Die Vorlesung beinhaltet folgende Themen: - Entity-Relationship Modell und komplexe Objekte - Relationenmodell und Relationenalgebra , Überblick SQL - Transformationen von ER nach Relationen, Normalisierung - XML, DTD, XML-Schema, Info-Set, Namensräume - Metamodelle und Repository - RDF, RDF-S und Ontologien - UML - Petri Netze, Workflownetze - BPMN
Link:	C@MPUS

Modellierung

Lecture
2 Sh
SS 25

Number:	021101000
Lecturers:	Univ.-Prof. Dr.-Ing. Bernhard Mitschang apl. Prof. Dr. Holger Schwarz
Type:	Lecture
Semester hours:	2
Teaching Language:	German
Semester:	SS 25
Organisation:	Datenbanken und Informationssysteme
Content:	See German page
Link:	C@MPUS

Practical Course Information Systems: Data-intensive Computing

Exercise
4 Sh
SS 25

Number:	021188000
Lecturers:	Univ.-Prof. Dr.-Ing. Bernhard Mitschang apl. Prof. Dr. Holger Schwarz
Type:	Exercise
Semester hours:	4
Teaching Language:	English/German
Semester:	SS 25
Organisation:	Datenbanken und Informationssysteme
Content:	This practical course mainly focuses on data-intensive applications and how they process, analyze and store their data. Nowadays, the amount of data in applications is growing intensely. This data can be either structured, e.g., stored in relational database systems such as MySQL, or unstructured, e.g., stored in text documents, pictures or other media files. Deriving information and, as a consequence, knowledge from this data is a huge challenge. To cope with this issue, new data analytics and data storage technologies have been developed that focus on the one hand on deriving information from this large amount of structured and unstructured data (e.g., data mining, natural language processing, ...) and on the other hand on efficient data storage (e.g., NoSQL databases, column-stores, ...). Modern web technologies are used to provide the web frontend and to visualize huge data sets and analytic results. Furthermore, to enable fast, efficient application development as well as a high degree of accessibility, flexibility and scalability, cloud computing platforms are oftentimes used to implement such applications. In this practical course, you will work in small teams. Each team will implement a new or extend an existing data-intensive application based on tasks that typically involve data analysis, data visualization, data storage and efficient data processing. The used infrastructure, e.g. a cloud-based infrastructure like IBM Cloud, depends on the application.
Link:	C@MPUS

Practical Course Information Systems: Data-intensive Computing

Exercise
4 Sh
SS 25

Number:	021188000
Lecturers:	Univ.-Prof. Dr.-Ing. Bernhard Mitschang apl. Prof. Dr. Holger Schwarz
Type:	Exercise
Semester hours:	4
Teaching Language:	English/German
Semester:	SS 25
Organisation:	Datenbanken und Informationssysteme
Content:	This practical course mainly focuses on data-intensive applications and how they process, analyze and store their data. Nowadays, the amount of data in applications is growing intensely. This data can be either structured, e.g., stored in relational database systems such as MySQL, or unstructured, e.g., stored in text documents, pictures or other media files. Deriving information and, as a consequence, knowledge from this data is a huge challenge. To cope with this issue, new data analytics and data storage technologies have been developed that focus on the one hand on deriving information from this large amount of structured and unstructured data (e.g., data mining, natural language processing, ...) and on the other hand on efficient data storage (e.g., NoSQL databases, column-stores, ...). Modern web technologies are used to provide the web frontend and to visualize huge data sets and analytic results. Furthermore, to enable fast, efficient application development as well as a high degree of accessibility, flexibility and scalability, cloud computing platforms are oftentimes used to implement such applications. In this practical course, you will work in small teams. Each team will implement a new or extend an existing data-intensive application based on tasks that typically involve data analysis, data visualization, data storage and efficient data processing. The used infrastructure, e.g. a cloud-based infrastructure like IBM Cloud, depends on the application.
Link:	C@MPUS

Vertiefungsthemen von Data Science

Seminar
2 Sh
SS 25

Number:	021190000
Lecturers:	Univ.-Prof. Dr.-Ing. Bernhard Mitschang apl. Prof. Dr. Holger Schwarz Dr. rer. nat. Christoph Stach
Type:	Seminar
Semester hours:	2
Teaching Language:	German
Semester:	SS 25
Organisation:	Datenbanken und Informationssysteme
Link:	C@MPUS

Vertiefungsthemen von Data Science

Seminar
2 Sh
SS 25

Number:	021190000
Lecturers:	Univ.-Prof. Dr.-Ing. Bernhard Mitschang apl. Prof. Dr. Holger Schwarz Dr. rer. nat. Christoph Stach
Type:	Seminar
Semester hours:	2
Teaching Language:	German
Semester:	SS 25
Organisation:	Datenbanken und Informationssysteme
Link:	C@MPUS

Additional current courses

Here, we provide information on additional courses that are not listed in Campus.

Study projects: currently not available
Development projects: currently not available
Project Data Science: Summer Term 2024

This overview shows the courses typically offered by the department in one year.

Bachelor

Einführung in Data Science: Lecture in the winter term (in German)
Modellierung: Lecture in the summer term (in German)
Seminars and Projects: Seminars, projects and similar courses are offered on a irregular basis (typically in German)

Master

Datenbanken und Informationssysteme: Lecture in the winter term (in German)
Data Warehouse, Data Mining and OLAP: Lecture in the winter term (in English)
Advanced Information Management: Lecture in the summer term (in English)
Vertiefungslinie Datenbanken und Informationssysteme: Among others, the lectures Datenbanken und Informationssysteme, Data Warehouse, Data Mining and OLAP and Advanced Information Management are part of this Vertiefungslinie
Advanced seminars, practical courses, projects: Advanced seminars, practical courses, projects and similar courses are offered on a irregular basis (Language: German or English)

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Current Courses of the Department (as listed in Campus)

Advanced Information Management

Advanced Information Management

Advanced Information Management

Advanced Information Management

Data Science mit Python

Data Science mit Python

Data Science mit Python

Data Science mit Python

GSaME-Kolloquium

GSaME-Kolloquium

Industrial Analytics

Industrial Analytics

Industrial Analytics

Industrial Analytics

Kolloquium Datenbanksysteme

Kolloquium Datenbanksysteme

Modellierung

Modellierung

Modellierung

Modellierung

Practical Course Information Systems: Data-intensive Computing

Practical Course Information Systems: Data-intensive Computing

Vertiefungsthemen von Data Science

Vertiefungsthemen von Data Science

Additional current courses

Bachelor

Master

Open and Current Student Projects

Exams

Stuttgart Data Management Academy

Bernhard Mitschang

Holger Schwarz

Eva Strähle

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Audience

Formalities

Services

Organization