AG Keim - Datenanalyse und Visualisierung

Fähigkeiten Section

Teaching by the Keim Research Group

Through the teaching offerings of the Data Analysis and Visualization Research Group (DBVIS) at the University of Konstanz, students acquire hands-on knowledge in data analysis, machine learning, and data visualization. Below you will find the regular courses offered by the Keim research group. In this way, we optimally prepare students for a career in industry and research.

Teaching in the Winter Term

Applications for Powerwall and Virtual Reality Environments

-Lecture- In this course, you’ll use advanced technology to create innovative visualizations, analysis techniques, and interaction methods for real-world datasets.

Data Mining: Basic Concepts

-Lecture- The students are taught elementary theoretical knowledge and get first practical experience in data analysis. They obtain the ability to assess requirements and parameters for the application of fundamental analysis algorithms.

Data Visualization: Advanced Topics

-Lecture- This course covers advanced visualization techniques for complex data. Students learn to evaluate and compare visualization methods, suggest alternative displays for challenging datasets, and implement basic visualizations.

Geographic Information Systems

-Lecture- Students learn to handle geospatial data, apply spatial indexing, computational geometry, and core GIS concepts (data types, analysis methods). They’ll assess system performance, break down complex tasks, and create tailored solutions.

Teaching in the Summer Term

Applied Visual Analytics

-Lecture- Learn to become a data scientist! Working with complex datasets, you and your team will develop an interactive visualization tool for the VAST Challenge, competing for awards and showcasing analytical skills.

Data Visualization: Basic Concepts

-Lecture- Gives an introduction to the field of Data Visualization. In particular, covering foundations, relevant aspects of human perception, visualization design principles, and some basic visualization techniques for different data types.

Multimedia Retrieval: Basic Concepts

-Lecture- Students learn the basics of similarity modeling and feature extraction in multimedia databases, focusing on image retrieval. Participants apply, develop, and refine algorithms for effective similarity searches within these systems.

Programming Workshop 2

-Lab- In this programming Workshop, students are assisted in solving Problems that they might come across during the PK2 lecture. This lecture only serves as aid, no solutions are presented.

Teaching

Teaching by the Keim Research Group

Teaching in the Winter Term

Applications for Powerwall and Virtual Reality Environments

Data Mining: Basic Concepts

Data Visualization: Advanced Topics

Geographic Information Systems

Teaching in the Summer Term

Applied Visual Analytics

Data Visualization: Basic Concepts

Multimedia Retrieval: Basic Concepts

Programming Workshop 2

Teaching Across both Terms

Our Seminars

Our Projects

Transferable Skills in Computer Science

Programming Workshop 1

Programming Practice Tutorial

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