After successful completion of the course, students are able to understand and implement advanced real-time visualization concepts. They are able to design and implement interactive systems to visually analyze large and complex data. 

In particular, the aims and scope of the course are: 

• learn advanced theoretical concepts and algorithms for real-time visualization (e.g., in-situ visualization, parallel rendering & visualization, scalable visual analytics approaches, advanced volume rendering techniques)
• learn practical skills in programming on graphics hardware (e.g., shader programming, GPGPU computing, distributed visualization, real-time visualization on the web using WebGL and WebGPU)
• see bleeding edge real-time visualization applications (e.g., molecular visualization, flood simulation and visualization) 
• implement a real-time visualization project (i.e., interactive visualization of a very large dataset). 

More detailed information, the detailed schedule, and all course materials can be found on TUWEL. 

• Frontal lectures about theoretical concepts and algorithms with slides. 
• Tutorial lectures about about graphics programming techniques (CUDA, WebGPU). 
• Guest lectures about domain-specific real-time visualization (e.g., molecular visualization, flood simulation and visualization). 
• Real-time visualization project in pairs (implementation and presentation). 

ECTS breakdown:  3 ECTS = 75 hours

37.5 hours - implementation, presentation, and documentation of the lab assignment

37.5 hours - lecture attendance and preparation for oral exam

Oral examination, project presentations, and submission interview.

Visualization knowledge and OpenGL programming skills