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 23

Number:	021152000
Lecturers:	Dennis Treder-Tschechlov apl. Prof. Dr. Holger Schwarz Dr. rer. nat. Pascal Hirmer
Type:	Exercise
Semester hours:	2
Teaching Language:	Englisd
Semester:	SS 23
Organisation:	Datenbanken und Informationssysteme
Content:	See lecture
Link:	C@MPUS

Advanced Information Management

Lecture
2 Sh
SS 23

Number:	021151000
Lecturers:	apl. Prof. Dr. Holger Schwarz
Type:	Lecture
Semester hours:	2
Teaching Language:	Englisd
Semester:	SS 23
Organisation:	Datenbanken und Informationssysteme
Content:	Die Vorlesung behandelt aktuelle Modellierungs-, Entwicklungs- und Verarbeitungskonzepte DB-basierter Anwendungssysteme. Hierzu gehört insbesondere die Verarbeitung strukturierter, semi-strukturierter und unstrukturierter Daten sowie Techniken zur Integration von Informationen aus heterogenen Datenquellen. Unter anderem werden folgende Themenbereiche vertieft: - XML und Datenbanktechnologie (XML-Modellierung, XML-Speicherung, XML-Anfragesprachen, - XML-Verarbeitung) - Content Management (Enterprise Content Management, Information Retrieval, Suchtechnologien) - NoSQL Datenmanagement (Key value stores, MapReduce, triple stores, document stores, graph stores)
Link:	C@MPUS

Advanced Information Management

Lecture
2 Sh
SS 23

Number:	021151000
Lecturers:	apl. Prof. Dr. Holger Schwarz
Type:	Lecture
Semester hours:	2
Teaching Language:	Englisd
Semester:	SS 23
Organisation:	Datenbanken und Informationssysteme
Content:	Die Vorlesung behandelt aktuelle Modellierungs-, Entwicklungs- und Verarbeitungskonzepte DB-basierter Anwendungssysteme. Hierzu gehört insbesondere die Verarbeitung strukturierter, semi-strukturierter und unstrukturierter Daten sowie Techniken zur Integration von Informationen aus heterogenen Datenquellen. Unter anderem werden folgende Themenbereiche vertieft: - XML und Datenbanktechnologie (XML-Modellierung, XML-Speicherung, XML-Anfragesprachen, - XML-Verarbeitung) - Content Management (Enterprise Content Management, Information Retrieval, Suchtechnologien) - NoSQL Datenmanagement (Key value stores, MapReduce, triple stores, document stores, graph stores)
Link:	C@MPUS

Advanced Information Management

Exercise
2 Sh
SS 23

Number:	021152000
Lecturers:	Dennis Treder-Tschechlov apl. Prof. Dr. Holger Schwarz Dr. rer. nat. Pascal Hirmer
Type:	Exercise
Semester hours:	2
Teaching Language:	Englisd
Semester:	SS 23
Organisation:	Datenbanken und Informationssysteme
Content:	See lecture
Link:	C@MPUS

Data Management for End-to-End Machine Learning

Advanced Seminar
2 Sh
SS 23

Number:	021195000
Lecturers:	apl. Prof. Dr. Holger Schwarz Univ.-Prof. Dr.-Ing. Bernhard Mitschang Dr. rer. nat. Peter Reimann
Type:	Advanced Seminar
Semester hours:	2
Teaching Language:	Englisd
Semester:	SS 23
Organisation:	Datenbanken und Informationssysteme
Content:	The comprehensive management of large volumes of data is crucial in modern information systems. This is often characterized by the term big data. Some of the main driving forces are current trends like Industrie 4.0 and the Internet of Things (IoT). In particular, the growing usage of sensors and the huge volume of data they are producing result in new challenges for large scale data management. These challenges refer to the entire lifecycle of IoT data including major steps like capturing, managing, processing and analyzing the data. Due to the General Data Protection Regulation (GDPR), data security and privacy have to be considered in all of these operations.
Link:	C@MPUS

Data Management for End-to-End Machine Learning

Advanced Seminar
2 Sh
SS 23

Number:	021195000
Lecturers:	apl. Prof. Dr. Holger Schwarz Univ.-Prof. Dr.-Ing. Bernhard Mitschang Dr. rer. nat. Peter Reimann
Type:	Advanced Seminar
Semester hours:	2
Teaching Language:	Englisd
Semester:	SS 23
Organisation:	Datenbanken und Informationssysteme
Content:	The comprehensive management of large volumes of data is crucial in modern information systems. This is often characterized by the term big data. Some of the main driving forces are current trends like Industrie 4.0 and the Internet of Things (IoT). In particular, the growing usage of sensors and the huge volume of data they are producing result in new challenges for large scale data management. These challenges refer to the entire lifecycle of IoT data including major steps like capturing, managing, processing and analyzing the data. Due to the General Data Protection Regulation (GDPR), data security and privacy have to be considered in all of these operations.
Link:	C@MPUS

Data Science mit Python

Lecture
1 Sh
SS 23

Number:	021100100
Lecturers:	Dr. rer. nat. Christoph Stach
Type:	Lecture
Semester hours:	1
Teaching Language:	German
Semester:	SS 23
Organisation:	Datenbanken und Informationssysteme
Content:	Datenakquise Datenbereinigung und –transformation Datenmodellierung Datenmanagement Datenverarbeitung Visualisierung von Analyseergebnissen
Link:	C@MPUS

Data Science mit Python

Exercise
3 Sh
SS 23

Number:	021100105
Lecturers:	Dr. rer. nat. Christoph Stach
Type:	Exercise
Semester hours:	3
Teaching Language:	German
Semester:	SS 23
Organisation:	Datenbanken und Informationssysteme
Content:	Siehe Vorlesung
Link:	C@MPUS

Data Science mit Python

Lecture
1 Sh
SS 23

Number:	021100100
Lecturers:	Dr. rer. nat. Christoph Stach
Type:	Lecture
Semester hours:	1
Teaching Language:	German
Semester:	SS 23
Organisation:	Datenbanken und Informationssysteme
Content:	Datenakquise Datenbereinigung und –transformation Datenmodellierung Datenmanagement Datenverarbeitung Visualisierung von Analyseergebnissen
Link:	C@MPUS

Data Science mit Python

Exercise
3 Sh
SS 23

Number:	021100105
Lecturers:	Dr. rer. nat. Christoph Stach
Type:	Exercise
Semester hours:	3
Teaching Language:	German
Semester:	SS 23
Organisation:	Datenbanken und Informationssysteme
Content:	Siehe Vorlesung
Link:	C@MPUS

GSaME-Kolloquium

Colloquium
2 Sh
SS 23

Number:	021198100
Lecturers:	Univ.-Prof. Dr.-Ing. Bernhard Mitschang
Type:	Colloquium
Semester hours:	2
Teaching Language:	German/Englisd
Semester:	SS 23
Organisation:	Datenbanken und Informationssysteme
Content:	for staff members and PhD students only
Link:	C@MPUS

GSaME-Kolloquium

Colloquium
2 Sh
SS 23

Number:	021198100
Lecturers:	Univ.-Prof. Dr.-Ing. Bernhard Mitschang
Type:	Colloquium
Semester hours:	2
Teaching Language:	German/Englisd
Semester:	SS 23
Organisation:	Datenbanken und Informationssysteme
Content:	for staff members and PhD students only
Link:	C@MPUS

Industrial Analytics

Exercise
1 Sh
SS 23

Number:	021100305
Lecturers:	Christoph Gröger
Type:	Exercise
Semester hours:	1
Teaching Language:	German
Semester:	SS 23
Organisation:	Datenbanken und Informationssysteme
Content:	See lecture
Link:	C@MPUS

Industrial Analytics

Exercise
1 Sh
SS 23

Number:	021100305
Lecturers:	Christoph Gröger
Type:	Exercise
Semester hours:	1
Teaching Language:	German
Semester:	SS 23
Organisation:	Datenbanken und Informationssysteme
Content:	See lecture
Link:	C@MPUS

Industrial Analytics

Lecture
1 Sh
SS 23

Number:	021100300
Lecturers:	Christoph Gröger
Type:	Lecture
Semester hours:	1
Teaching Language:	German
Semester:	SS 23
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 23

Number:	021100300
Lecturers:	Christoph Gröger
Type:	Lecture
Semester hours:	1
Teaching Language:	German
Semester:	SS 23
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

Kolloquium Datenbanksysteme

Colloquium
2 Sh
SS 23

Number:	021198000
Lecturers:	Univ.-Prof. Dr.-Ing. Bernhard Mitschang
Type:	Colloquium
Semester hours:	2
Teaching Language:	German/Englisd
Semester:	SS 23
Organisation:	Datenbanken und Informationssysteme
Content:	nur für Mitarbeiterinnen und Doktorandinnen
Link:	C@MPUS

Kolloquium Datenbanksysteme

Colloquium
2 Sh
SS 23

Number:	021198000
Lecturers:	Univ.-Prof. Dr.-Ing. Bernhard Mitschang
Type:	Colloquium
Semester hours:	2
Teaching Language:	German/Englisd
Semester:	SS 23
Organisation:	Datenbanken und Informationssysteme
Content:	nur für Mitarbeiterinnen und Doktorandinnen
Link:	C@MPUS

Modellierung

Exercise
2 Sh
SS 23

Number:	021102000
Lecturers:	apl. Prof. Dr. Holger Schwarz Daniel Vietz
Type:	Exercise
Semester hours:	2
Teaching Language:	German
Semester:	SS 23
Organisation:	Datenbanken und Informationssysteme
Content:	See German description
Link:	C@MPUS

Modellierung

Lecture
2 Sh
SS 23

Number:	021101000
Lecturers:	Univ.-Prof. Dr.-Ing. Bernhard Mitschang Dr. rer. nat. Karoline Wild
Type:	Lecture
Semester hours:	2
Teaching Language:	German
Semester:	SS 23
Organisation:	Datenbanken und Informationssysteme
Content:	See German page
Link:	C@MPUS

Modellierung

Lecture
2 Sh
SS 23

Number:	021101000
Lecturers:	Univ.-Prof. Dr.-Ing. Bernhard Mitschang Dr. rer. nat. Karoline Wild
Type:	Lecture
Semester hours:	2
Teaching Language:	German
Semester:	SS 23
Organisation:	Datenbanken und Informationssysteme
Content:	See German page
Link:	C@MPUS

Modellierung

Exercise
2 Sh
SS 23

Number:	021102000
Lecturers:	apl. Prof. Dr. Holger Schwarz Daniel Vietz
Type:	Exercise
Semester hours:	2
Teaching Language:	German
Semester:	SS 23
Organisation:	Datenbanken und Informationssysteme
Content:	See German description
Link:	C@MPUS

Practical Course Information Systems

Exercise
4 Sh
SS 23

Number:	021188000
Lecturers:	apl. Prof. Dr. Holger Schwarz Univ.-Prof. Dr.-Ing. Bernhard Mitschang
Type:	Exercise
Semester hours:	4
Teaching Language:	Englisd/German
Semester:	SS 23
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

Exercise
4 Sh
SS 23

Number:	021188000
Lecturers:	apl. Prof. Dr. Holger Schwarz Univ.-Prof. Dr.-Ing. Bernhard Mitschang
Type:	Exercise
Semester hours:	4
Teaching Language:	Englisd/German
Semester:	SS 23
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 Data Science

Seminar
2 Sh
SS 23

Number:	021185000
Lecturers:	Dr. rer. nat. Christoph Stach apl. Prof. Dr. Holger Schwarz Univ.-Prof. Dr.-Ing. Bernhard Mitschang
Type:	Seminar
Semester hours:	2
Teaching Language:	German
Semester:	SS 23
Organisation:	Datenbanken und Informationssysteme
Content:	https://www.f05.uni-stuttgart.de/informatik/dokumente/Seminare/Seminare_23S/08_Sem-Vertiefung-DS.pdf
Link:	C@MPUS

Vertiefungsthemen Data Science

Seminar
2 Sh
SS 23

Number:	021185000
Lecturers:	Dr. rer. nat. Christoph Stach apl. Prof. Dr. Holger Schwarz Univ.-Prof. Dr.-Ing. Bernhard Mitschang
Type:	Seminar
Semester hours:	2
Teaching Language:	German
Semester:	SS 23
Organisation:	Datenbanken und Informationssysteme
Content:	https://www.f05.uni-stuttgart.de/informatik/dokumente/Seminare/Seminare_23S/08_Sem-Vertiefung-DS.pdf
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: Winter term 2022/2023

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 Management for End-to-End Machine Learning

Data Management for End-to-End Machine Learning

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

Practical Course Information Systems

Vertiefungsthemen Data Science

Vertiefungsthemen Data Science

Additional current courses

Bachelor

Master

Open and Current Student Projects

Exams

Stuttgart Data Management Academy

Bernhard Mitschang

Holger Schwarz

Eva Strähle

Here you can reach us

Audience

Formalities

Services

Organization